Overview

Dataset statistics

Number of variables62
Number of observations114
Missing cells2830
Missing cells (%)40.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory55.3 KiB
Average record size in memory497.1 B

Variable types

Numeric12
Categorical41
Unsupported9

Alerts

airdate has constant value "2020-12-15" Constant
_embedded.show.externals.tvrage has constant value "19056.0" Constant
url has a high cardinality: 114 distinct values High cardinality
name has a high cardinality: 113 distinct values High cardinality
summary has a high cardinality: 54 distinct values High cardinality
_links.self.href has a high cardinality: 114 distinct values High cardinality
_embedded.show.url has a high cardinality: 71 distinct values High cardinality
_embedded.show.name has a high cardinality: 71 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 61 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 65 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 68 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 68 distinct values High cardinality
_embedded.show.summary has a high cardinality: 63 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 71 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 71 distinct values High cardinality
image.medium has a high cardinality: 55 distinct values High cardinality
image.original has a high cardinality: 55 distinct values High cardinality
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 2 other fieldsHigh correlation
rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.averageHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 1 other fieldsHigh correlation
number is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 2 other fieldsHigh correlation
rating.average is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.id is highly correlated with number and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with number and 5 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
id is highly correlated with _embedded.show.idHigh correlation
season is highly correlated with _embedded.show.externals.thetvdbHigh correlation
number is highly correlated with _embedded.show.rating.averageHigh correlation
runtime is highly correlated with rating.average and 2 other fieldsHigh correlation
rating.average is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with number and 5 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.updatedHigh correlation
id is highly correlated with airtime and 37 other fieldsHigh correlation
season is highly correlated with number and 22 other fieldsHigh correlation
number is highly correlated with season and 29 other fieldsHigh correlation
type is highly correlated with summary and 16 other fieldsHigh correlation
airtime is highly correlated with id and 36 other fieldsHigh correlation
airstamp is highly correlated with id and 37 other fieldsHigh correlation
runtime is highly correlated with id and 39 other fieldsHigh correlation
summary is highly correlated with id and 42 other fieldsHigh correlation
rating.average is highly correlated with airstamp and 20 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with type and 30 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with number and 28 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 43 other fieldsHigh correlation
image.medium is highly correlated with id and 41 other fieldsHigh correlation
image.original is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 27 other fieldsHigh correlation
number has 3 (2.6%) missing values Missing
runtime has 6 (5.3%) missing values Missing
image has 114 (100.0%) missing values Missing
summary has 60 (52.6%) missing values Missing
rating.average has 111 (97.4%) missing values Missing
_embedded.show.runtime has 51 (44.7%) missing values Missing
_embedded.show.averageRuntime has 4 (3.5%) missing values Missing
_embedded.show.ended has 55 (48.2%) missing values Missing
_embedded.show.officialSite has 6 (5.3%) missing values Missing
_embedded.show.rating.average has 107 (93.9%) missing values Missing
_embedded.show.network has 114 (100.0%) missing values Missing
_embedded.show.webChannel.id has 4 (3.5%) missing values Missing
_embedded.show.webChannel.name has 4 (3.5%) missing values Missing
_embedded.show.webChannel.country.name has 79 (69.3%) missing values Missing
_embedded.show.webChannel.country.code has 79 (69.3%) missing values Missing
_embedded.show.webChannel.country.timezone has 79 (69.3%) missing values Missing
_embedded.show.webChannel.officialSite has 34 (29.8%) missing values Missing
_embedded.show.dvdCountry has 114 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 113 (99.1%) missing values Missing
_embedded.show.externals.thetvdb has 60 (52.6%) missing values Missing
_embedded.show.externals.imdb has 74 (64.9%) missing values Missing
_embedded.show.image.medium has 3 (2.6%) missing values Missing
_embedded.show.image.original has 3 (2.6%) missing values Missing
_embedded.show.summary has 8 (7.0%) missing values Missing
_embedded.show.webChannel.country has 114 (100.0%) missing values Missing
image.medium has 59 (51.8%) missing values Missing
image.original has 59 (51.8%) missing values Missing
_embedded.show.network.id has 105 (92.1%) missing values Missing
_embedded.show.network.name has 105 (92.1%) missing values Missing
_embedded.show.network.country.name has 105 (92.1%) missing values Missing
_embedded.show.network.country.code has 105 (92.1%) missing values Missing
_embedded.show.network.country.timezone has 105 (92.1%) missing values Missing
_embedded.show.network.officialSite has 114 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 109 (95.6%) missing values Missing
_embedded.show.image has 114 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 112 (98.2%) missing values Missing
_embedded.show.dvdCountry.code has 112 (98.2%) missing values Missing
_embedded.show.dvdCountry.timezone has 112 (98.2%) missing values Missing
_embedded.show.webChannel has 114 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.externals.imdb is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.dvdCountry.name is uniformly distributed Uniform
_embedded.show.dvdCountry.code is uniformly distributed Uniform
_embedded.show.dvdCountry.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-05 04:39:47.523018
Analysis finished2022-09-05 04:40:03.296473
Duration15.77 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2058505.316
Minimum1960498
Maximum2380807
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:03.340715image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1960498
5-th percentile1974836.45
Q11986148.25
median2017107.5
Q32092977.75
95-th percentile2288517.1
Maximum2380807
Range420309
Interquartile range (IQR)106829.5

Descriptive statistics

Standard deviation96637.20682
Coefficient of variation (CV)0.0469453278
Kurtosis2.323383809
Mean2058505.316
Median Absolute Deviation (MAD)47839
Skewness1.527445733
Sum234669606
Variance9338749742
MonotonicityNot monotonic
2022-09-04T23:40:03.423711image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19888601
 
0.9%
20929791
 
0.9%
20929771
 
0.9%
20929761
 
0.9%
20929751
 
0.9%
20929741
 
0.9%
20929731
 
0.9%
20929721
 
0.9%
20929711
 
0.9%
20929701
 
0.9%
Other values (104)104
91.2%
ValueCountFrequency (%)
19604981
0.9%
19643331
0.9%
19645671
0.9%
19680021
0.9%
19705351
0.9%
19726051
0.9%
19760381
0.9%
19760391
0.9%
19761601
0.9%
19761611
0.9%
ValueCountFrequency (%)
23808071
0.9%
23799291
0.9%
23745021
0.9%
23181051
0.9%
23110191
0.9%
22898731
0.9%
22877871
0.9%
22396091
0.9%
22152351
0.9%
21972831
0.9%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/episodes/1988860/sim-for-you-4x22-chanyeols-episode-22
 
1
https://www.tvmaze.com/episodes/2092979/90-day-fiance-extras-1x23-tania-syngin-our-journey-so-far
 
1
https://www.tvmaze.com/episodes/2092977/90-day-fiance-extras-1x21-david-annie-the-full-story
 
1
https://www.tvmaze.com/episodes/2092976/90-day-fiance-extras-1x20-darceys-continuing-journey
 
1
https://www.tvmaze.com/episodes/2092975/90-day-fiance-extras-1x19-angela-michael-our-continuing-journey
 
1
Other values (109)
109 

Length

Max length134
Median length96.5
Mean length85.52631579
Min length58

Characters and Unicode

Total characters9750
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1988860/sim-for-you-4x22-chanyeols-episode-22
2nd rowhttps://www.tvmaze.com/episodes/1987445/serlok-v-rossii-s01-special-film-o-filme
3rd rowhttps://www.tvmaze.com/episodes/2007749/stand-up-autsajd-1x09-irina-prihodko-skvirt
4th rowhttps://www.tvmaze.com/episodes/2008029/lab-s-antonom-belaevym-2x08-elena-temnikova
5th rowhttps://www.tvmaze.com/episodes/1964567/core-sense-1x11-episode-11

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988860/sim-for-you-4x22-chanyeols-episode-221
 
0.9%
https://www.tvmaze.com/episodes/2092979/90-day-fiance-extras-1x23-tania-syngin-our-journey-so-far1
 
0.9%
https://www.tvmaze.com/episodes/2092977/90-day-fiance-extras-1x21-david-annie-the-full-story1
 
0.9%
https://www.tvmaze.com/episodes/2092976/90-day-fiance-extras-1x20-darceys-continuing-journey1
 
0.9%
https://www.tvmaze.com/episodes/2092975/90-day-fiance-extras-1x19-angela-michael-our-continuing-journey1
 
0.9%
https://www.tvmaze.com/episodes/2092974/90-day-fiance-extras-1x18-tiffany-ronald-our-journey-so-far1
 
0.9%
https://www.tvmaze.com/episodes/2092973/90-day-fiance-extras-1x17-deavan-jihoon-our-journey-so-far1
 
0.9%
https://www.tvmaze.com/episodes/2092972/90-day-fiance-extras-1x16-jenny-sumit-our-journey-so-far1
 
0.9%
https://www.tvmaze.com/episodes/2092971/90-day-fiance-extras-1x15-angela-michael-our-journey-so-far1
 
0.9%
https://www.tvmaze.com/episodes/2092970/90-day-fiance-extras-1x14-darcey-jesse-our-journey-so-far1
 
0.9%
Other values (104)104
91.2%

Length

2022-09-04T23:40:03.525746image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988860/sim-for-you-4x22-chanyeols-episode-221
 
0.9%
https://www.tvmaze.com/episodes/2003908/10-glupyh-voprosov-2020-12-15-anton-kozubov-fizik-teoretik1
 
0.9%
https://www.tvmaze.com/episodes/2008029/lab-s-antonom-belaevym-2x08-elena-temnikova1
 
0.9%
https://www.tvmaze.com/episodes/1964567/core-sense-1x11-episode-111
 
0.9%
https://www.tvmaze.com/episodes/2052509/wu-shen-zhu-zai-1x84-episode-841
 
0.9%
https://www.tvmaze.com/episodes/2096297/no-turning-back-romance-1x03-31
 
0.9%
https://www.tvmaze.com/episodes/2071479/youths-in-the-breeze-1x09-people-from-the-story-011
 
0.9%
https://www.tvmaze.com/episodes/2071480/youths-in-the-breeze-1x10-people-from-the-story-021
 
0.9%
https://www.tvmaze.com/episodes/2082175/ling-jian-zun-4x32-di132ji1
 
0.9%
https://www.tvmaze.com/episodes/2161416/mafia-nights-2x02-bazy-dwm-grwh-dwm1
 
0.9%
Other values (104)104
91.2%

Most occurring characters

ValueCountFrequency (%)
e824
 
8.5%
-824
 
8.5%
s572
 
5.9%
/570
 
5.8%
t561
 
5.8%
o499
 
5.1%
a484
 
5.0%
w381
 
3.9%
i371
 
3.8%
m317
 
3.3%
Other values (29)4347
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6645
68.2%
Decimal Number1369
 
14.0%
Other Punctuation912
 
9.4%
Dash Punctuation824
 
8.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e824
 
12.4%
s572
 
8.6%
t561
 
8.4%
o499
 
7.5%
a484
 
7.3%
w381
 
5.7%
i371
 
5.6%
m317
 
4.8%
p303
 
4.6%
d272
 
4.1%
Other values (15)2061
31.0%
Decimal Number
ValueCountFrequency (%)
1260
19.0%
2231
16.9%
0219
16.0%
9208
15.2%
888
 
6.4%
786
 
6.3%
379
 
5.8%
668
 
5.0%
568
 
5.0%
462
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/570
62.5%
.228
 
25.0%
:114
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-824
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6645
68.2%
Common3105
31.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e824
 
12.4%
s572
 
8.6%
t561
 
8.4%
o499
 
7.5%
a484
 
7.3%
w381
 
5.7%
i371
 
5.6%
m317
 
4.8%
p303
 
4.6%
d272
 
4.1%
Other values (15)2061
31.0%
Common
ValueCountFrequency (%)
-824
26.5%
/570
18.4%
1260
 
8.4%
2231
 
7.4%
.228
 
7.3%
0219
 
7.1%
9208
 
6.7%
:114
 
3.7%
888
 
2.8%
786
 
2.8%
Other values (4)277
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII9750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e824
 
8.5%
-824
 
8.5%
s572
 
5.9%
/570
 
5.8%
t561
 
5.8%
o499
 
5.1%
a484
 
5.0%
w381
 
3.9%
i371
 
3.8%
m317
 
3.3%
Other values (29)4347
44.6%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct113
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Episode 11
 
2
Chanyeol's Episode 22
 
1
Ashley & Jay: Our Journey So Far
 
1
Colt & Larissa: Our Continuing Journey
 
1
David & Annie: The Full Story
 
1
Other values (108)
108 

Length

Max length68
Median length37
Mean length23.25438596
Min length1

Characters and Unicode

Total characters2651
Distinct characters137
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)98.2%

Sample

1st rowChanyeol's Episode 22
2nd rowФильм о фильме
3rd rowИрина Приходько "Сквирт"
4th rowЕлена Темникова
5th rowEpisode 11

Common Values

ValueCountFrequency (%)
Episode 112
 
1.8%
Chanyeol's Episode 221
 
0.9%
Ashley & Jay: Our Journey So Far1
 
0.9%
Colt & Larissa: Our Continuing Journey1
 
0.9%
David & Annie: The Full Story1
 
0.9%
Darcey's Continuing Journey1
 
0.9%
Angela & Michael: Our Continuing Journey1
 
0.9%
Tiffany & Ronald: Our Journey So Far1
 
0.9%
Deavan & Jihoon: Our Journey So Far1
 
0.9%
Jenny & Sumit: Our Journey So Far1
 
0.9%
Other values (103)103
90.4%

Length

2022-09-04T23:40:03.624009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
36
 
7.4%
episode22
 
4.5%
journey21
 
4.3%
our20
 
4.1%
the16
 
3.3%
so15
 
3.1%
far15
 
3.1%
continuing5
 
1.0%
story5
 
1.0%
love4
 
0.8%
Other values (275)325
67.1%

Most occurring characters

ValueCountFrequency (%)
370
 
14.0%
e210
 
7.9%
o136
 
5.1%
a136
 
5.1%
r130
 
4.9%
i126
 
4.8%
n123
 
4.6%
s84
 
3.2%
u82
 
3.1%
t72
 
2.7%
Other values (127)1182
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1646
62.1%
Uppercase Letter430
 
16.2%
Space Separator370
 
14.0%
Decimal Number88
 
3.3%
Other Punctuation83
 
3.1%
Other Letter16
 
0.6%
Dash Punctuation11
 
0.4%
Close Punctuation3
 
0.1%
Open Punctuation3
 
0.1%
Math Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e210
12.8%
o136
 
8.3%
a136
 
8.3%
r130
 
7.9%
i126
 
7.7%
n123
 
7.5%
s84
 
5.1%
u82
 
5.0%
t72
 
4.4%
l66
 
4.0%
Other values (47)481
29.2%
Uppercase Letter
ValueCountFrequency (%)
E40
 
9.3%
S31
 
7.2%
J28
 
6.5%
O27
 
6.3%
F26
 
6.0%
T24
 
5.6%
M21
 
4.9%
A21
 
4.9%
D20
 
4.7%
C19
 
4.4%
Other values (34)173
40.2%
Other Letter
ValueCountFrequency (%)
و3
18.8%
م2
12.5%
د2
12.5%
ب1
 
6.2%
1
 
6.2%
1
 
6.2%
ه1
 
6.2%
ر1
 
6.2%
گ1
 
6.2%
ی1
 
6.2%
Other values (2)2
12.5%
Decimal Number
ValueCountFrequency (%)
122
25.0%
218
20.5%
310
11.4%
010
11.4%
47
 
8.0%
86
 
6.8%
55
 
5.7%
95
 
5.7%
63
 
3.4%
72
 
2.3%
Other Punctuation
ValueCountFrequency (%)
:29
34.9%
&25
30.1%
'7
 
8.4%
,5
 
6.0%
?5
 
6.0%
.5
 
6.0%
!3
 
3.6%
"2
 
2.4%
#2
 
2.4%
Space Separator
ValueCountFrequency (%)
370
100.0%
Dash Punctuation
ValueCountFrequency (%)
-11
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Math Symbol
ValueCountFrequency (%)
|1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1872
70.6%
Common559
 
21.1%
Cyrillic204
 
7.7%
Arabic14
 
0.5%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e210
 
11.2%
o136
 
7.3%
a136
 
7.3%
r130
 
6.9%
i126
 
6.7%
n123
 
6.6%
s84
 
4.5%
u82
 
4.4%
t72
 
3.8%
l66
 
3.5%
Other values (42)707
37.8%
Cyrillic
ValueCountFrequency (%)
о18
 
8.8%
и17
 
8.3%
е11
 
5.4%
а11
 
5.4%
н9
 
4.4%
к9
 
4.4%
р9
 
4.4%
в7
 
3.4%
Е7
 
3.4%
Т7
 
3.4%
Other values (39)99
48.5%
Common
ValueCountFrequency (%)
370
66.2%
:29
 
5.2%
&25
 
4.5%
122
 
3.9%
218
 
3.2%
-11
 
2.0%
310
 
1.8%
010
 
1.8%
47
 
1.3%
'7
 
1.3%
Other values (14)50
 
8.9%
Arabic
ValueCountFrequency (%)
و3
21.4%
م2
14.3%
د2
14.3%
ب1
 
7.1%
ه1
 
7.1%
ر1
 
7.1%
گ1
 
7.1%
ی1
 
7.1%
ز1
 
7.1%
ا1
 
7.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2426
91.5%
Cyrillic204
 
7.7%
Arabic14
 
0.5%
None5
 
0.2%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
370
 
15.3%
e210
 
8.7%
o136
 
5.6%
a136
 
5.6%
r130
 
5.4%
i126
 
5.2%
n123
 
5.1%
s84
 
3.5%
u82
 
3.4%
t72
 
3.0%
Other values (61)957
39.4%
Cyrillic
ValueCountFrequency (%)
о18
 
8.8%
и17
 
8.3%
е11
 
5.4%
а11
 
5.4%
н9
 
4.4%
к9
 
4.4%
р9
 
4.4%
в7
 
3.4%
Е7
 
3.4%
Т7
 
3.4%
Other values (39)99
48.5%
Arabic
ValueCountFrequency (%)
و3
21.4%
م2
14.3%
د2
14.3%
ب1
 
7.1%
ه1
 
7.1%
ر1
 
7.1%
گ1
 
7.1%
ی1
 
7.1%
ز1
 
7.1%
ا1
 
7.1%
None
ValueCountFrequency (%)
í1
20.0%
ø1
20.0%
ü1
20.0%
ö1
20.0%
á1
20.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean232.3508772
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:03.705838image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)2

Descriptive statistics

Standard deviation644.1886848
Coefficient of variation (CV)2.772482259
Kurtosis4.128587636
Mean232.3508772
Median Absolute Deviation (MAD)0
Skewness2.460925035
Sum26488
Variance414979.0616
MonotonicityNot monotonic
2022-09-04T23:40:03.772076image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
170
61.4%
202013
 
11.4%
212
 
10.5%
46
 
5.3%
36
 
5.3%
73
 
2.6%
101
 
0.9%
121
 
0.9%
181
 
0.9%
311
 
0.9%
ValueCountFrequency (%)
170
61.4%
212
 
10.5%
36
 
5.3%
46
 
5.3%
73
 
2.6%
101
 
0.9%
121
 
0.9%
181
 
0.9%
311
 
0.9%
202013
 
11.4%
ValueCountFrequency (%)
202013
 
11.4%
311
 
0.9%
181
 
0.9%
121
 
0.9%
101
 
0.9%
73
 
2.6%
46
 
5.3%
36
 
5.3%
212
 
10.5%
170
61.4%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct50
Distinct (%)45.0%
Missing3
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean30.35135135
Minimum1
Maximum342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:03.858610image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16.5
median15
Q328.5
95-th percentile101.5
Maximum342
Range341
Interquartile range (IQR)22

Descriptive statistics

Standard deviation54.66902873
Coefficient of variation (CV)1.801205755
Kurtosis19.52443629
Mean30.35135135
Median Absolute Deviation (MAD)11
Skewness4.222574201
Sum3369
Variance2988.702703
MonotonicityNot monotonic
2022-09-04T23:40:03.953594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38
 
7.0%
47
 
6.1%
96
 
5.3%
26
 
5.3%
85
 
4.4%
105
 
4.4%
213
 
2.6%
63
 
2.6%
283
 
2.6%
273
 
2.6%
Other values (40)62
54.4%
ValueCountFrequency (%)
12
 
1.8%
26
5.3%
38
7.0%
47
6.1%
52
 
1.8%
63
 
2.6%
73
 
2.6%
85
4.4%
96
5.3%
105
4.4%
ValueCountFrequency (%)
3421
0.9%
3041
0.9%
3031
0.9%
1521
0.9%
1431
0.9%
1021
0.9%
1011
0.9%
841
0.9%
731
0.9%
661
0.9%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
regular
111 
insignificant_special
 
2
significant_special
 
1

Length

Max length21
Median length7
Mean length7.350877193
Min length7

Characters and Unicode

Total characters838
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowregular
2nd rowinsignificant_special
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular111
97.4%
insignificant_special2
 
1.8%
significant_special1
 
0.9%

Length

2022-09-04T23:40:04.154891image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:04.228835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
regular111
97.4%
insignificant_special2
 
1.8%
significant_special1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
r222
26.5%
a117
14.0%
e114
13.6%
g114
13.6%
l114
13.6%
u111
13.2%
i14
 
1.7%
n8
 
1.0%
s6
 
0.7%
c6
 
0.7%
Other values (4)12
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter835
99.6%
Connector Punctuation3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r222
26.6%
a117
14.0%
e114
13.7%
g114
13.7%
l114
13.7%
u111
13.3%
i14
 
1.7%
n8
 
1.0%
s6
 
0.7%
c6
 
0.7%
Other values (3)9
 
1.1%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin835
99.6%
Common3
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
r222
26.6%
a117
14.0%
e114
13.7%
g114
13.7%
l114
13.7%
u111
13.3%
i14
 
1.7%
n8
 
1.0%
s6
 
0.7%
c6
 
0.7%
Other values (3)9
 
1.1%
Common
ValueCountFrequency (%)
_3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r222
26.5%
a117
14.0%
e114
13.6%
g114
13.6%
l114
13.6%
u111
13.2%
i14
 
1.7%
n8
 
1.0%
s6
 
0.7%
c6
 
0.7%
Other values (4)12
 
1.4%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-15
114 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1140
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-15
2nd row2020-12-15
3rd row2020-12-15
4th row2020-12-15
5th row2020-12-15

Common Values

ValueCountFrequency (%)
2020-12-15114
100.0%

Length

2022-09-04T23:40:04.299848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:04.366848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-15114
100.0%

Most occurring characters

ValueCountFrequency (%)
2342
30.0%
0228
20.0%
-228
20.0%
1228
20.0%
5114
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number912
80.0%
Dash Punctuation228
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2342
37.5%
0228
25.0%
1228
25.0%
5114
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2342
30.0%
0228
20.0%
-228
20.0%
1228
20.0%
5114
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2342
30.0%
0228
20.0%
-228
20.0%
1228
20.0%
5114
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
88 
20:00
13 
06:00
 
2
10:00
 
2
20:40
 
2
Other values (7)
 
7

Length

Max length5
Median length0
Mean length1.140350877
Min length0

Characters and Unicode

Total characters130
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)6.1%

Sample

1st row06:00
2nd row
3rd row12:00
4th row
5th row10:00

Common Values

ValueCountFrequency (%)
88
77.2%
20:0013
 
11.4%
06:002
 
1.8%
10:002
 
1.8%
20:402
 
1.8%
12:001
 
0.9%
08:001
 
0.9%
17:001
 
0.9%
17:351
 
0.9%
22:001
 
0.9%
Other values (2)2
 
1.8%

Length

2022-09-04T23:40:04.426848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0013
50.0%
06:002
 
7.7%
10:002
 
7.7%
20:402
 
7.7%
12:001
 
3.8%
08:001
 
3.8%
17:001
 
3.8%
17:351
 
3.8%
22:001
 
3.8%
00:251
 
3.8%

Most occurring characters

ValueCountFrequency (%)
068
52.3%
:26
 
20.0%
219
 
14.6%
16
 
4.6%
53
 
2.3%
62
 
1.5%
42
 
1.5%
72
 
1.5%
81
 
0.8%
31
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number104
80.0%
Other Punctuation26
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
068
65.4%
219
 
18.3%
16
 
5.8%
53
 
2.9%
62
 
1.9%
42
 
1.9%
72
 
1.9%
81
 
1.0%
31
 
1.0%
Other Punctuation
ValueCountFrequency (%)
:26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
068
52.3%
:26
 
20.0%
219
 
14.6%
16
 
4.6%
53
 
2.3%
62
 
1.5%
42
 
1.5%
72
 
1.5%
81
 
0.8%
31
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
068
52.3%
:26
 
20.0%
219
 
14.6%
16
 
4.6%
53
 
2.3%
62
 
1.5%
42
 
1.5%
72
 
1.5%
81
 
0.8%
31
 
0.8%

airstamp
Categorical

HIGH CORRELATION

Distinct19
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-15T12:00:00+00:00
84 
2020-12-15T17:00:00+00:00
 
4
2020-12-15T04:00:00+00:00
 
3
2020-12-15T00:00:00+00:00
 
3
2020-12-15T11:00:00+00:00
 
3
Other values (14)
17 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2850
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)9.6%

Sample

1st row2020-12-14T21:00:00+00:00
2nd row2020-12-15T00:00:00+00:00
3rd row2020-12-15T00:00:00+00:00
4th row2020-12-15T00:00:00+00:00
5th row2020-12-15T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-15T12:00:00+00:0084
73.7%
2020-12-15T17:00:00+00:004
 
3.5%
2020-12-15T04:00:00+00:003
 
2.6%
2020-12-15T00:00:00+00:003
 
2.6%
2020-12-15T11:00:00+00:003
 
2.6%
2020-12-15T02:00:00+00:002
 
1.8%
2020-12-15T19:40:00+00:002
 
1.8%
2020-12-15T05:00:00+00:002
 
1.8%
2020-12-14T21:00:00+00:001
 
0.9%
2020-12-15T14:00:00+00:001
 
0.9%
Other values (9)9
 
7.9%

Length

2022-09-04T23:40:04.495848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-15t12:00:00+00:0084
73.7%
2020-12-15t17:00:00+00:004
 
3.5%
2020-12-15t04:00:00+00:003
 
2.6%
2020-12-15t00:00:00+00:003
 
2.6%
2020-12-15t11:00:00+00:003
 
2.6%
2020-12-15t02:00:00+00:002
 
1.8%
2020-12-15t19:40:00+00:002
 
1.8%
2020-12-15t05:00:00+00:002
 
1.8%
2020-12-15t13:00:00+00:001
 
0.9%
2020-12-15t03:00:00+00:001
 
0.9%
Other values (9)9
 
7.9%

Most occurring characters

ValueCountFrequency (%)
01152
40.4%
2431
 
15.1%
:342
 
12.0%
1329
 
11.5%
-228
 
8.0%
5119
 
4.2%
T114
 
4.0%
+114
 
4.0%
48
 
0.3%
75
 
0.2%
Other values (2)8
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2052
72.0%
Other Punctuation342
 
12.0%
Dash Punctuation228
 
8.0%
Uppercase Letter114
 
4.0%
Math Symbol114
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01152
56.1%
2431
 
21.0%
1329
 
16.0%
5119
 
5.8%
48
 
0.4%
75
 
0.2%
94
 
0.2%
34
 
0.2%
Other Punctuation
ValueCountFrequency (%)
:342
100.0%
Dash Punctuation
ValueCountFrequency (%)
-228
100.0%
Uppercase Letter
ValueCountFrequency (%)
T114
100.0%
Math Symbol
ValueCountFrequency (%)
+114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2736
96.0%
Latin114
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01152
42.1%
2431
 
15.8%
:342
 
12.5%
1329
 
12.0%
-228
 
8.3%
5119
 
4.3%
+114
 
4.2%
48
 
0.3%
75
 
0.2%
94
 
0.1%
Latin
ValueCountFrequency (%)
T114
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01152
40.4%
2431
 
15.1%
:342
 
12.0%
1329
 
11.5%
-228
 
8.0%
5119
 
4.2%
T114
 
4.0%
+114
 
4.0%
48
 
0.3%
75
 
0.2%
Other values (2)8
 
0.3%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct45
Distinct (%)41.7%
Missing6
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean50.92592593
Minimum5
Maximum126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:04.572989image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.35
Q122.75
median45
Q381.25
95-th percentile123.65
Maximum126
Range121
Interquartile range (IQR)58.5

Descriptive statistics

Standard deviation37.709094
Coefficient of variation (CV)0.7404694821
Kurtosis-0.5686340402
Mean50.92592593
Median Absolute Deviation (MAD)25.5
Skewness0.801007587
Sum5500
Variance1421.97577
MonotonicityNot monotonic
2022-09-04T23:40:04.668961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
4517
 
14.9%
827
 
6.1%
235
 
4.4%
1244
 
3.5%
124
 
3.5%
304
 
3.5%
243
 
2.6%
253
 
2.6%
1203
 
2.6%
53
 
2.6%
Other values (35)55
48.2%
(Missing)6
 
5.3%
ValueCountFrequency (%)
53
2.6%
61
 
0.9%
72
1.8%
81
 
0.9%
91
 
0.9%
102
1.8%
112
1.8%
124
3.5%
141
 
0.9%
151
 
0.9%
ValueCountFrequency (%)
1261
 
0.9%
1251
 
0.9%
1244
3.5%
1233
2.6%
1222
 
1.8%
1212
 
1.8%
1203
2.6%
902
 
1.8%
882
 
1.8%
827
6.1%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing114
Missing (%)100.0%
Memory size1.0 KiB

summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct54
Distinct (%)100.0%
Missing60
Missing (%)52.6%
Memory size1.0 KiB
<p>Angela had a turbulent romance with her younger Nigerian boyfriend, Michael. These are the most dramatic moments of their relationship.</p>
 
1
<p>After Jenny went to India to be with her boyfriend, Sumit, the couple have endured many ups and downs. These are their most dramatic moments.</p>
 
1
<p>Deavan became pregnant with Jihoon's baby and moved to South Korea to be closer to him. These are the highs and lows of their whirlwind romance.</p>
 
1
<p>It was after falling in love with her South African partner that Tiffany discovered his troublesome past. These are their most dramatic moments.</p>
 
1
<p>Angela and Michael met online and fell in love, but their relationship hasn't been easy. These are their most dramatic moments.</p>
 
1
Other values (49)
49 

Length

Max length1001
Median length157
Mean length176.5
Min length47

Characters and Unicode

Total characters9531
Distinct characters80
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st row<p><b>#Hidden Map Open #Blue Ocean View</b></p>
2nd row<p>Lord of the Rings: Fellowship of the Ring Comedy Recap dubbed with the voices of HISHE.</p>
3rd row<p>It's a Returning the Favor Special! @MikeRowe and team celebrate the first 100 do-gooders featured on Returning the Favor and Mike shares his personal journey and lessons he's learned as host of the series.</p>
4th row<p>Elizaveta Boyarskaya talks frankly about her rare film shootings, family, feminism, the female role, her husband Maxim Matveyev, her attempt to move to Moscow, her complexes, her famous father, the hype, theater and Danil Kozlovsky. </p>
5th row<p>Erica Durance (Smallville, Saving Hope) joins me this week to share the anxiety and stress of going behind the scenes working in casting to in front of the camera on Smallville. Erica opens up on the different ways that she's felt that she didn't belong both in her personal and professional life. We also get into her thoughts and experience with postpartum, different tools to overcome anxiety, and her opinions on the Arrowverse.</p>

Common Values

ValueCountFrequency (%)
<p>Angela had a turbulent romance with her younger Nigerian boyfriend, Michael. These are the most dramatic moments of their relationship.</p>1
 
0.9%
<p>After Jenny went to India to be with her boyfriend, Sumit, the couple have endured many ups and downs. These are their most dramatic moments.</p>1
 
0.9%
<p>Deavan became pregnant with Jihoon's baby and moved to South Korea to be closer to him. These are the highs and lows of their whirlwind romance.</p>1
 
0.9%
<p>It was after falling in love with her South African partner that Tiffany discovered his troublesome past. These are their most dramatic moments.</p>1
 
0.9%
<p>Angela and Michael met online and fell in love, but their relationship hasn't been easy. These are their most dramatic moments.</p>1
 
0.9%
<p>After her breakup with Jesse, Darcey continued her quest for Mr Right and found love with dapper British gent, Tom. These are her most dramatic moments.</p>1
 
0.9%
<p>American David and Annie from Thailand have a 24-year age difference, but their love is undeniable. Can they overcome all the stresses of married life?</p>1
 
0.9%
<p>Revealing all the highs and lows in Colt and Larissa's tumultuous relationship. From arguments with his mum to an emergency call to the police.</p>1
 
0.9%
<p>After moving to America to be with Tania, Syngin felt abandoned moved to Costa Rica. These are the dramatic moments from their love story.</p>1
 
0.9%
<p>Kalani met her boyfriend Asuelu in Samoa, and he moved to the USA after she fell pregnant with their first child. This is their dramatic story.</p>1
 
0.9%
Other values (44)44
38.6%
(Missing)60
52.6%

Length

2022-09-04T23:40:04.772396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the82
 
5.2%
and72
 
4.6%
to57
 
3.6%
with30
 
1.9%
in29
 
1.9%
her28
 
1.8%
of27
 
1.7%
their24
 
1.5%
a22
 
1.4%
from16
 
1.0%
Other values (722)1179
75.3%

Most occurring characters

ValueCountFrequency (%)
1505
15.8%
e909
 
9.5%
a608
 
6.4%
t597
 
6.3%
o533
 
5.6%
i497
 
5.2%
n481
 
5.0%
r463
 
4.9%
s453
 
4.8%
h382
 
4.0%
Other values (70)3103
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7091
74.4%
Space Separator1513
 
15.9%
Other Punctuation325
 
3.4%
Uppercase Letter321
 
3.4%
Math Symbol250
 
2.6%
Decimal Number19
 
0.2%
Dash Punctuation10
 
0.1%
Open Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e909
12.8%
a608
 
8.6%
t597
 
8.4%
o533
 
7.5%
i497
 
7.0%
n481
 
6.8%
r463
 
6.5%
s453
 
6.4%
h382
 
5.4%
l313
 
4.4%
Other values (19)1855
26.2%
Uppercase Letter
ValueCountFrequency (%)
A34
 
10.6%
R34
 
10.6%
T26
 
8.1%
M24
 
7.5%
C23
 
7.2%
S19
 
5.9%
D18
 
5.6%
L16
 
5.0%
P15
 
4.7%
K13
 
4.0%
Other values (14)99
30.8%
Other Punctuation
ValueCountFrequency (%)
.96
29.5%
,79
24.3%
'66
20.3%
/65
20.0%
?8
 
2.5%
!5
 
1.5%
#2
 
0.6%
:1
 
0.3%
@1
 
0.3%
&1
 
0.3%
Decimal Number
ValueCountFrequency (%)
05
26.3%
94
21.1%
12
 
10.5%
72
 
10.5%
42
 
10.5%
22
 
10.5%
81
 
5.3%
31
 
5.3%
Space Separator
ValueCountFrequency (%)
1505
99.5%
 8
 
0.5%
Math Symbol
ValueCountFrequency (%)
>125
50.0%
<125
50.0%
Dash Punctuation
ValueCountFrequency (%)
-9
90.0%
1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7412
77.8%
Common2119
 
22.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e909
12.3%
a608
 
8.2%
t597
 
8.1%
o533
 
7.2%
i497
 
6.7%
n481
 
6.5%
r463
 
6.2%
s453
 
6.1%
h382
 
5.2%
l313
 
4.2%
Other values (43)2176
29.4%
Common
ValueCountFrequency (%)
1505
71.0%
>125
 
5.9%
<125
 
5.9%
.96
 
4.5%
,79
 
3.7%
'66
 
3.1%
/65
 
3.1%
-9
 
0.4%
 8
 
0.4%
?8
 
0.4%
Other values (17)33
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII9516
99.8%
None14
 
0.1%
Punctuation1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1505
15.8%
e909
 
9.6%
a608
 
6.4%
t597
 
6.3%
o533
 
5.6%
i497
 
5.2%
n481
 
5.1%
r463
 
4.9%
s453
 
4.8%
h382
 
4.0%
Other values (65)3088
32.5%
None
ValueCountFrequency (%)
 8
57.1%
é3
 
21.4%
à2
 
14.3%
è1
 
7.1%
Punctuation
ValueCountFrequency (%)
1
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing111
Missing (%)97.4%
Memory size1.0 KiB
9.0
7.5
7.3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row9.0
2nd row7.5
3rd row7.3

Common Values

ValueCountFrequency (%)
9.01
 
0.9%
7.51
 
0.9%
7.31
 
0.9%
(Missing)111
97.4%

Length

2022-09-04T23:40:04.861323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:04.940165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
9.01
33.3%
7.51
33.3%
7.31
33.3%

Most occurring characters

ValueCountFrequency (%)
.3
33.3%
72
22.2%
91
 
11.1%
01
 
11.1%
51
 
11.1%
31
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
66.7%
Other Punctuation3
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
72
33.3%
91
16.7%
01
16.7%
51
16.7%
31
16.7%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.3
33.3%
72
22.2%
91
 
11.1%
01
 
11.1%
51
 
11.1%
31
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.3
33.3%
72
22.2%
91
 
11.1%
01
 
11.1%
51
 
11.1%
31
 
11.1%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/1988860
 
1
https://api.tvmaze.com/episodes/2092979
 
1
https://api.tvmaze.com/episodes/2092977
 
1
https://api.tvmaze.com/episodes/2092976
 
1
https://api.tvmaze.com/episodes/2092975
 
1
Other values (109)
109 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4446
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988860
2nd rowhttps://api.tvmaze.com/episodes/1987445
3rd rowhttps://api.tvmaze.com/episodes/2007749
4th rowhttps://api.tvmaze.com/episodes/2008029
5th rowhttps://api.tvmaze.com/episodes/1964567

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888601
 
0.9%
https://api.tvmaze.com/episodes/20929791
 
0.9%
https://api.tvmaze.com/episodes/20929771
 
0.9%
https://api.tvmaze.com/episodes/20929761
 
0.9%
https://api.tvmaze.com/episodes/20929751
 
0.9%
https://api.tvmaze.com/episodes/20929741
 
0.9%
https://api.tvmaze.com/episodes/20929731
 
0.9%
https://api.tvmaze.com/episodes/20929721
 
0.9%
https://api.tvmaze.com/episodes/20929711
 
0.9%
https://api.tvmaze.com/episodes/20929701
 
0.9%
Other values (104)104
91.2%

Length

2022-09-04T23:40:05.007517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888601
 
0.9%
https://api.tvmaze.com/episodes/20039081
 
0.9%
https://api.tvmaze.com/episodes/20080291
 
0.9%
https://api.tvmaze.com/episodes/19645671
 
0.9%
https://api.tvmaze.com/episodes/20525091
 
0.9%
https://api.tvmaze.com/episodes/20962971
 
0.9%
https://api.tvmaze.com/episodes/20714791
 
0.9%
https://api.tvmaze.com/episodes/20714801
 
0.9%
https://api.tvmaze.com/episodes/20821751
 
0.9%
https://api.tvmaze.com/episodes/21614161
 
0.9%
Other values (104)104
91.2%

Most occurring characters

ValueCountFrequency (%)
/456
 
10.3%
p342
 
7.7%
s342
 
7.7%
e342
 
7.7%
t342
 
7.7%
o228
 
5.1%
a228
 
5.1%
i228
 
5.1%
.228
 
5.1%
m228
 
5.1%
Other values (16)1482
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2850
64.1%
Other Punctuation798
 
17.9%
Decimal Number798
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p342
12.0%
s342
12.0%
e342
12.0%
t342
12.0%
o228
8.0%
a228
8.0%
i228
8.0%
m228
8.0%
h114
 
4.0%
d114
 
4.0%
Other values (3)342
12.0%
Decimal Number
ValueCountFrequency (%)
9161
20.2%
2125
15.7%
1102
12.8%
094
11.8%
872
9.0%
772
9.0%
655
 
6.9%
342
 
5.3%
541
 
5.1%
434
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/456
57.1%
.228
28.6%
:114
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2850
64.1%
Common1596
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/456
28.6%
.228
14.3%
9161
 
10.1%
2125
 
7.8%
:114
 
7.1%
1102
 
6.4%
094
 
5.9%
872
 
4.5%
772
 
4.5%
655
 
3.4%
Other values (3)117
 
7.3%
Latin
ValueCountFrequency (%)
p342
12.0%
s342
12.0%
e342
12.0%
t342
12.0%
o228
8.0%
a228
8.0%
i228
8.0%
m228
8.0%
h114
 
4.0%
d114
 
4.0%
Other values (3)342
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/456
 
10.3%
p342
 
7.7%
s342
 
7.7%
e342
 
7.7%
t342
 
7.7%
o228
 
5.1%
a228
 
5.1%
i228
 
5.1%
.228
 
5.1%
m228
 
5.1%
Other values (16)1482
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct71
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49165.62281
Minimum2504
Maximum63761
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:05.091106image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile17848.15
Q149166.25
median52468
Q355355
95-th percentile59985.5
Maximum63761
Range61257
Interquartile range (IQR)6188.75

Descriptive statistics

Standard deviation11521.26559
Coefficient of variation (CV)0.2343358008
Kurtosis4.364730768
Mean49165.62281
Median Absolute Deviation (MAD)2887
Skewness-2.130480772
Sum5604881
Variance132739560.8
MonotonicityNot monotonic
2022-09-04T23:40:05.183293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5535532
28.1%
506164
 
3.5%
521082
 
1.8%
525242
 
1.8%
524002
 
1.8%
547622
 
1.8%
521592
 
1.8%
521072
 
1.8%
521042
 
1.8%
501062
 
1.8%
Other values (61)62
54.4%
ValueCountFrequency (%)
25041
0.9%
133811
0.9%
133921
0.9%
152502
1.8%
176331
0.9%
179641
0.9%
214911
0.9%
262681
0.9%
306061
0.9%
320871
0.9%
ValueCountFrequency (%)
637611
0.9%
637191
0.9%
617551
0.9%
615301
0.9%
608091
0.9%
607851
0.9%
595551
0.9%
583671
0.9%
573391
0.9%
572851
0.9%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct71
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/shows/55355/90-day-fiance-extras
32 
https://www.tvmaze.com/shows/50616/song-exploder
 
4
https://www.tvmaze.com/shows/52108/psych-hunter
 
2
https://www.tvmaze.com/shows/52524/forever-love
 
2
https://www.tvmaze.com/shows/52400/dream-detective
 
2
Other values (66)
72 

Length

Max length71
Median length66
Mean length51.52631579
Min length40

Characters and Unicode

Total characters5874
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)52.6%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/49422/serlok-v-rossii
3rd rowhttps://www.tvmaze.com/shows/51065/stand-up-autsajd
4th rowhttps://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym
5th rowhttps://www.tvmaze.com/shows/51336/core-sense

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/55355/90-day-fiance-extras32
28.1%
https://www.tvmaze.com/shows/50616/song-exploder4
 
3.5%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
1.8%
https://www.tvmaze.com/shows/52524/forever-love2
 
1.8%
https://www.tvmaze.com/shows/52400/dream-detective2
 
1.8%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
1.8%
https://www.tvmaze.com/shows/52159/to-love2
 
1.8%
https://www.tvmaze.com/shows/52107/new-face2
 
1.8%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
1.8%
https://www.tvmaze.com/shows/50106/cheyenne-et-lola2
 
1.8%
Other values (61)62
54.4%

Length

2022-09-04T23:40:05.283227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/55355/90-day-fiance-extras32
28.1%
https://www.tvmaze.com/shows/50616/song-exploder4
 
3.5%
https://www.tvmaze.com/shows/52159/to-love2
 
1.8%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
1.8%
https://www.tvmaze.com/shows/50106/cheyenne-et-lola2
 
1.8%
https://www.tvmaze.com/shows/52107/new-face2
 
1.8%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
1.8%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
1.8%
https://www.tvmaze.com/shows/52400/dream-detective2
 
1.8%
https://www.tvmaze.com/shows/52524/forever-love2
 
1.8%
Other values (61)62
54.4%

Most occurring characters

ValueCountFrequency (%)
/570
 
9.7%
w474
 
8.1%
t452
 
7.7%
s445
 
7.6%
e324
 
5.5%
o313
 
5.3%
a302
 
5.1%
h272
 
4.6%
m259
 
4.4%
-231
 
3.9%
Other values (29)2232
38.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4091
69.6%
Other Punctuation912
 
15.5%
Decimal Number640
 
10.9%
Dash Punctuation231
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w474
11.6%
t452
11.0%
s445
10.9%
e324
 
7.9%
o313
 
7.7%
a302
 
7.4%
h272
 
6.6%
m259
 
6.3%
c179
 
4.4%
v143
 
3.5%
Other values (15)928
22.7%
Decimal Number
ValueCountFrequency (%)
5197
30.8%
079
12.3%
371
 
11.1%
957
 
8.9%
153
 
8.3%
249
 
7.7%
447
 
7.3%
642
 
6.6%
823
 
3.6%
722
 
3.4%
Other Punctuation
ValueCountFrequency (%)
/570
62.5%
.228
 
25.0%
:114
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-231
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4091
69.6%
Common1783
30.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w474
11.6%
t452
11.0%
s445
10.9%
e324
 
7.9%
o313
 
7.7%
a302
 
7.4%
h272
 
6.6%
m259
 
6.3%
c179
 
4.4%
v143
 
3.5%
Other values (15)928
22.7%
Common
ValueCountFrequency (%)
/570
32.0%
-231
13.0%
.228
 
12.8%
5197
 
11.0%
:114
 
6.4%
079
 
4.4%
371
 
4.0%
957
 
3.2%
153
 
3.0%
249
 
2.7%
Other values (4)134
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII5874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/570
 
9.7%
w474
 
8.1%
t452
 
7.7%
s445
 
7.6%
e324
 
5.5%
o313
 
5.3%
a302
 
5.1%
h272
 
4.6%
m259
 
4.4%
-231
 
3.9%
Other values (29)2232
38.0%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct71
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
90 Day Fiancé: Extras
32 
Song Exploder
 
4
Psych Hunter
 
2
Forever Love
 
2
Dream Detective
 
2
Other values (66)
72 

Length

Max length36
Median length28
Mean length16.9122807
Min length5

Characters and Unicode

Total characters1928
Distinct characters100
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)52.6%

Sample

1st rowSim for You
2nd rowШерлок в России
3rd rowStand Up Аутсайд
4th rowLAB с Антоном Беляевым
5th rowCore Sense

Common Values

ValueCountFrequency (%)
90 Day Fiancé: Extras32
28.1%
Song Exploder4
 
3.5%
Psych Hunter2
 
1.8%
Forever Love2
 
1.8%
Dream Detective2
 
1.8%
Youths in the Breeze2
 
1.8%
To Love2
 
1.8%
New Face2
 
1.8%
Twisted Fate of Love2
 
1.8%
Cheyenne et Lola2
 
1.8%
Other values (61)62
54.4%

Length

2022-09-04T23:40:05.381774image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9032
 
9.3%
fiancé32
 
9.3%
extras32
 
9.3%
day32
 
9.3%
the8
 
2.3%
love7
 
2.0%
song4
 
1.2%
exploder4
 
1.2%
of4
 
1.2%
in3
 
0.9%
Other values (163)187
54.2%

Most occurring characters

ValueCountFrequency (%)
231
 
12.0%
a165
 
8.6%
e127
 
6.6%
n90
 
4.7%
r89
 
4.6%
i88
 
4.6%
t83
 
4.3%
o74
 
3.8%
s70
 
3.6%
c52
 
2.7%
Other values (90)859
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1284
66.6%
Uppercase Letter300
 
15.6%
Space Separator231
 
12.0%
Decimal Number71
 
3.7%
Other Punctuation40
 
2.1%
Dash Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a165
12.9%
e127
 
9.9%
n90
 
7.0%
r89
 
6.9%
i88
 
6.9%
t83
 
6.5%
o74
 
5.8%
s70
 
5.5%
c52
 
4.0%
y44
 
3.4%
Other values (43)402
31.3%
Uppercase Letter
ValueCountFrequency (%)
D43
14.3%
F42
14.0%
E41
13.7%
S24
 
8.0%
T22
 
7.3%
A12
 
4.0%
L12
 
4.0%
C11
 
3.7%
H10
 
3.3%
B10
 
3.3%
Other values (22)73
24.3%
Decimal Number
ValueCountFrequency (%)
034
47.9%
932
45.1%
22
 
2.8%
11
 
1.4%
41
 
1.4%
71
 
1.4%
Other Punctuation
ValueCountFrequency (%)
:33
82.5%
'3
 
7.5%
/1
 
2.5%
.1
 
2.5%
,1
 
2.5%
!1
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
1
50.0%
-1
50.0%
Space Separator
ValueCountFrequency (%)
231
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1481
76.8%
Common344
 
17.8%
Cyrillic103
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a165
 
11.1%
e127
 
8.6%
n90
 
6.1%
r89
 
6.0%
i88
 
5.9%
t83
 
5.6%
o74
 
5.0%
s70
 
4.7%
c52
 
3.5%
y44
 
3.0%
Other values (41)599
40.4%
Cyrillic
ValueCountFrequency (%)
о10
 
9.7%
е9
 
8.7%
с7
 
6.8%
в6
 
5.8%
р6
 
5.8%
а5
 
4.9%
п5
 
4.9%
т5
 
4.9%
и5
 
4.9%
н4
 
3.9%
Other values (24)41
39.8%
Common
ValueCountFrequency (%)
231
67.2%
034
 
9.9%
:33
 
9.6%
932
 
9.3%
'3
 
0.9%
22
 
0.6%
1
 
0.3%
11
 
0.3%
41
 
0.3%
71
 
0.3%
Other values (5)5
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1790
92.8%
Cyrillic103
 
5.3%
None34
 
1.8%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
 
12.9%
a165
 
9.2%
e127
 
7.1%
n90
 
5.0%
r89
 
5.0%
i88
 
4.9%
t83
 
4.6%
o74
 
4.1%
s70
 
3.9%
c52
 
2.9%
Other values (52)721
40.3%
None
ValueCountFrequency (%)
é32
94.1%
ø1
 
2.9%
ı1
 
2.9%
Cyrillic
ValueCountFrequency (%)
о10
 
9.7%
е9
 
8.7%
с7
 
6.8%
в6
 
5.8%
р6
 
5.8%
а5
 
4.9%
п5
 
4.9%
т5
 
4.9%
и5
 
4.9%
н4
 
3.9%
Other values (24)41
39.8%
Punctuation
ValueCountFrequency (%)
1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Scripted
37 
Reality
36 
Talk Show
14 
Documentary
11 
Animation
Other values (3)
10 

Length

Max length11
Median length9
Mean length7.956140351
Min length4

Characters and Unicode

Total characters907
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReality
2nd rowScripted
3rd rowVariety
4th rowDocumentary
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted37
32.5%
Reality36
31.6%
Talk Show14
 
12.3%
Documentary11
 
9.6%
Animation6
 
5.3%
Variety4
 
3.5%
News3
 
2.6%
Sports3
 
2.6%

Length

2022-09-04T23:40:05.475159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:05.565592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted37
28.9%
reality36
28.1%
talk14
 
10.9%
show14
 
10.9%
documentary11
 
8.6%
animation6
 
4.7%
variety4
 
3.1%
news3
 
2.3%
sports3
 
2.3%

Most occurring characters

ValueCountFrequency (%)
t97
 
10.7%
e91
 
10.0%
i89
 
9.8%
a71
 
7.8%
r55
 
6.1%
S54
 
6.0%
y51
 
5.6%
l50
 
5.5%
c48
 
5.3%
p40
 
4.4%
Other values (16)261
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter765
84.3%
Uppercase Letter128
 
14.1%
Space Separator14
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t97
12.7%
e91
11.9%
i89
11.6%
a71
9.3%
r55
7.2%
y51
 
6.7%
l50
 
6.5%
c48
 
6.3%
p40
 
5.2%
d37
 
4.8%
Other values (8)136
17.8%
Uppercase Letter
ValueCountFrequency (%)
S54
42.2%
R36
28.1%
T14
 
10.9%
D11
 
8.6%
A6
 
4.7%
V4
 
3.1%
N3
 
2.3%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin893
98.5%
Common14
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t97
 
10.9%
e91
 
10.2%
i89
 
10.0%
a71
 
8.0%
r55
 
6.2%
S54
 
6.0%
y51
 
5.7%
l50
 
5.6%
c48
 
5.4%
p40
 
4.5%
Other values (15)247
27.7%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII907
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t97
 
10.7%
e91
 
10.0%
i89
 
9.8%
a71
 
7.8%
r55
 
6.1%
S54
 
6.0%
y51
 
5.6%
l50
 
5.5%
c48
 
5.3%
p40
 
4.4%
Other values (16)261
28.8%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct16
Distinct (%)14.2%
Missing1
Missing (%)0.9%
Memory size1.0 KiB
English
63 
Chinese
18 
Russian
11 
Korean
 
4
Norwegian
 
4
Other values (11)
13 

Length

Max length10
Median length7
Mean length7.053097345
Min length5

Characters and Unicode

Total characters797
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)8.0%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowChinese

Common Values

ValueCountFrequency (%)
English63
55.3%
Chinese18
 
15.8%
Russian11
 
9.6%
Korean4
 
3.5%
Norwegian4
 
3.5%
Japanese2
 
1.8%
French2
 
1.8%
German1
 
0.9%
Turkish1
 
0.9%
Vietnamese1
 
0.9%
Other values (6)6
 
5.3%

Length

2022-09-04T23:40:05.651592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english63
55.8%
chinese18
 
15.9%
russian11
 
9.7%
korean4
 
3.5%
norwegian4
 
3.5%
japanese2
 
1.8%
french2
 
1.8%
german1
 
0.9%
turkish1
 
0.9%
vietnamese1
 
0.9%
Other values (6)6
 
5.3%

Most occurring characters

ValueCountFrequency (%)
s110
13.8%
n108
13.6%
i101
12.7%
h86
10.8%
g70
8.8%
l64
8.0%
E63
7.9%
e57
7.2%
a30
 
3.8%
C18
 
2.3%
Other values (22)90
11.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter684
85.8%
Uppercase Letter113
 
14.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s110
16.1%
n108
15.8%
i101
14.8%
h86
12.6%
g70
10.2%
l64
9.4%
e57
8.3%
a30
 
4.4%
u15
 
2.2%
r15
 
2.2%
Other values (8)28
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
E63
55.8%
C18
 
15.9%
R11
 
9.7%
N4
 
3.5%
K4
 
3.5%
J2
 
1.8%
F2
 
1.8%
T2
 
1.8%
P2
 
1.8%
G1
 
0.9%
Other values (4)4
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin797
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s110
13.8%
n108
13.6%
i101
12.7%
h86
10.8%
g70
8.8%
l64
8.0%
E63
7.9%
e57
7.2%
a30
 
3.8%
C18
 
2.3%
Other values (22)90
11.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII797
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s110
13.8%
n108
13.6%
i101
12.7%
h86
10.8%
g70
8.8%
l64
8.0%
E63
7.9%
e57
7.2%
a30
 
3.8%
C18
 
2.3%
Other values (22)90
11.3%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Ended
59 
Running
43 
To Be Determined
12 

Length

Max length16
Median length5
Mean length6.912280702
Min length5

Characters and Unicode

Total characters788
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowTo Be Determined
3rd rowEnded
4th rowTo Be Determined
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended59
51.8%
Running43
37.7%
To Be Determined12
 
10.5%

Length

2022-09-04T23:40:05.724591image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:05.797826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ended59
42.8%
running43
31.2%
to12
 
8.7%
be12
 
8.7%
determined12
 
8.7%

Most occurring characters

ValueCountFrequency (%)
n200
25.4%
d130
16.5%
e107
13.6%
E59
 
7.5%
i55
 
7.0%
R43
 
5.5%
u43
 
5.5%
g43
 
5.5%
24
 
3.0%
T12
 
1.5%
Other values (6)72
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter626
79.4%
Uppercase Letter138
 
17.5%
Space Separator24
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n200
31.9%
d130
20.8%
e107
17.1%
i55
 
8.8%
u43
 
6.9%
g43
 
6.9%
o12
 
1.9%
t12
 
1.9%
r12
 
1.9%
m12
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
E59
42.8%
R43
31.2%
T12
 
8.7%
B12
 
8.7%
D12
 
8.7%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin764
97.0%
Common24
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n200
26.2%
d130
17.0%
e107
14.0%
E59
 
7.7%
i55
 
7.2%
R43
 
5.6%
u43
 
5.6%
g43
 
5.6%
T12
 
1.6%
o12
 
1.6%
Other values (5)60
 
7.9%
Common
ValueCountFrequency (%)
24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII788
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n200
25.4%
d130
16.5%
e107
13.6%
E59
 
7.5%
i55
 
7.0%
R43
 
5.5%
u43
 
5.5%
g43
 
5.5%
24
 
3.0%
T12
 
1.5%
Other values (6)72
 
9.1%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)39.7%
Missing51
Missing (%)44.7%
Infinite0
Infinite (%)0.0%
Mean36.57142857
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:05.865825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.1
Q120
median30
Q345
95-th percentile87
Maximum120
Range115
Interquartile range (IQR)25

Descriptive statistics

Standard deviation26.04135315
Coefficient of variation (CV)0.7120682501
Kurtosis3.216523897
Mean36.57142857
Median Absolute Deviation (MAD)15
Skewness1.538008988
Sum2304
Variance678.1520737
MonotonicityNot monotonic
2022-09-04T23:40:05.948103image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4514
 
12.3%
306
 
5.3%
54
 
3.5%
254
 
3.5%
604
 
3.5%
204
 
3.5%
1203
 
2.6%
572
 
1.8%
122
 
1.8%
162
 
1.8%
Other values (15)18
 
15.8%
(Missing)51
44.7%
ValueCountFrequency (%)
54
3.5%
61
 
0.9%
72
1.8%
81
 
0.9%
101
 
0.9%
122
1.8%
141
 
0.9%
151
 
0.9%
162
1.8%
204
3.5%
ValueCountFrequency (%)
1203
 
2.6%
901
 
0.9%
604
 
3.5%
572
 
1.8%
521
 
0.9%
502
 
1.8%
4514
12.3%
402
 
1.8%
351
 
0.9%
306
5.3%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct35
Distinct (%)31.8%
Missing4
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean51.18181818
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:06.152004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6.45
Q123.25
median45
Q391
95-th percentile91
Maximum120
Range115
Interquartile range (IQR)67.75

Descriptive statistics

Standard deviation33.88625924
Coefficient of variation (CV)0.6620761131
Kurtosis-1.366468891
Mean51.18181818
Median Absolute Deviation (MAD)32
Skewness0.2674297513
Sum5630
Variance1148.278565
MonotonicityNot monotonic
2022-09-04T23:40:06.244004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
9132
28.1%
4513
 
11.4%
267
 
6.1%
255
 
4.4%
124
 
3.5%
54
 
3.5%
1203
 
2.6%
603
 
2.6%
143
 
2.6%
62
 
1.8%
Other values (25)34
29.8%
(Missing)4
 
3.5%
ValueCountFrequency (%)
54
3.5%
62
1.8%
72
1.8%
81
 
0.9%
91
 
0.9%
101
 
0.9%
112
1.8%
124
3.5%
143
2.6%
162
1.8%
ValueCountFrequency (%)
1203
 
2.6%
9132
28.1%
902
 
1.8%
871
 
0.9%
611
 
0.9%
603
 
2.6%
591
 
0.9%
571
 
0.9%
561
 
0.9%
511
 
0.9%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct61
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-15
32 
2020-11-24
 
4
2020-10-02
 
4
2020-11-23
 
4
2020-12-14
 
3
Other values (56)
67 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1140
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)43.0%

Sample

1st row2019-03-25
2nd row2020-10-22
3rd row2020-10-13
4th row2019-12-17
5th row2020-10-13

Common Values

ValueCountFrequency (%)
2020-12-1532
28.1%
2020-11-244
 
3.5%
2020-10-024
 
3.5%
2020-11-234
 
3.5%
2020-12-143
 
2.6%
2020-10-133
 
2.6%
2020-12-083
 
2.6%
2020-12-013
 
2.6%
2020-10-203
 
2.6%
2020-12-132
 
1.8%
Other values (51)53
46.5%

Length

2022-09-04T23:40:06.329004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1532
28.1%
2020-10-024
 
3.5%
2020-11-234
 
3.5%
2020-11-244
 
3.5%
2020-12-143
 
2.6%
2020-10-133
 
2.6%
2020-12-083
 
2.6%
2020-12-013
 
2.6%
2020-10-203
 
2.6%
2013-12-242
 
1.8%
Other values (51)53
46.5%

Most occurring characters

ValueCountFrequency (%)
0279
24.5%
2274
24.0%
-228
20.0%
1205
18.0%
543
 
3.8%
327
 
2.4%
926
 
2.3%
822
 
1.9%
417
 
1.5%
714
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number912
80.0%
Dash Punctuation228
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0279
30.6%
2274
30.0%
1205
22.5%
543
 
4.7%
327
 
3.0%
926
 
2.9%
822
 
2.4%
417
 
1.9%
714
 
1.5%
65
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
-228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0279
24.5%
2274
24.0%
-228
20.0%
1205
18.0%
543
 
3.8%
327
 
2.4%
926
 
2.3%
822
 
1.9%
417
 
1.5%
714
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0279
24.5%
2274
24.0%
-228
20.0%
1205
18.0%
543
 
3.8%
327
 
2.4%
926
 
2.3%
822
 
1.9%
417
 
1.5%
714
 
1.2%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)23.7%
Missing55
Missing (%)48.2%
Memory size1.0 KiB
2020-12-15
34 
2020-12-22
2021-01-05
2020-12-30
 
2
2020-12-16
 
2
Other values (9)
10 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters590
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)13.6%

Sample

1st row2020-12-31
2nd row2021-01-06
3rd row2020-12-22
4th row2020-12-22
5th row2020-12-24

Common Values

ValueCountFrequency (%)
2020-12-1534
29.8%
2020-12-226
 
5.3%
2021-01-055
 
4.4%
2020-12-302
 
1.8%
2020-12-162
 
1.8%
2020-12-232
 
1.8%
2020-12-311
 
0.9%
2021-01-061
 
0.9%
2020-12-241
 
0.9%
2021-11-111
 
0.9%
Other values (4)4
 
3.5%
(Missing)55
48.2%

Length

2022-09-04T23:40:06.402714image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1534
57.6%
2020-12-226
 
10.2%
2021-01-055
 
8.5%
2020-12-302
 
3.4%
2020-12-162
 
3.4%
2020-12-232
 
3.4%
2020-12-311
 
1.7%
2021-01-061
 
1.7%
2020-12-241
 
1.7%
2021-11-111
 
1.7%
Other values (4)4
 
6.8%

Most occurring characters

ValueCountFrequency (%)
2186
31.5%
0125
21.2%
-118
20.0%
1107
18.1%
539
 
6.6%
35
 
0.8%
64
 
0.7%
42
 
0.3%
92
 
0.3%
71
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number472
80.0%
Dash Punctuation118
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2186
39.4%
0125
26.5%
1107
22.7%
539
 
8.3%
35
 
1.1%
64
 
0.8%
42
 
0.4%
92
 
0.4%
71
 
0.2%
81
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common590
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2186
31.5%
0125
21.2%
-118
20.0%
1107
18.1%
539
 
6.6%
35
 
0.8%
64
 
0.7%
42
 
0.3%
92
 
0.3%
71
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2186
31.5%
0125
21.2%
-118
20.0%
1107
18.1%
539
 
6.6%
35
 
0.8%
64
 
0.7%
42
 
0.3%
92
 
0.3%
71
 
0.2%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct65
Distinct (%)60.2%
Missing6
Missing (%)5.3%
Memory size1.0 KiB
https://www.discoveryplus.co.uk/show/90-day-extras
32 
https://www.netflix.com/title/80992997
 
4
https://v.qq.com/detail/m/mzc00200tu76tos.html
 
2
https://v.qq.com/detail/m/mzc00200dnvb1wh.html
 
2
https://v.qq.com/detail/m/mzc00200ur8p8zp.html
 
2
Other values (60)
66 

Length

Max length105
Median length75.5
Mean length50.41666667
Min length18

Characters and Unicode

Total characters5445
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)50.0%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://start.ru/watch/sherlok-v-rossii
3rd rowhttps://premier.one/show/13734
4th rowhttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva
5th rowhttps://www.bilibili.com/bangumi/media/md28223064

Common Values

ValueCountFrequency (%)
https://www.discoveryplus.co.uk/show/90-day-extras32
28.1%
https://www.netflix.com/title/809929974
 
3.5%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
1.8%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
1.8%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
1.8%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
1.8%
https://www.tytnetwork.com2
 
1.8%
https://www.iqiyi.com/a_19rrhskr95.html2
 
1.8%
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
1.8%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
1.8%
Other values (55)56
49.1%
(Missing)6
 
5.3%

Length

2022-09-04T23:40:06.493626image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.discoveryplus.co.uk/show/90-day-extras32
29.6%
https://www.netflix.com/title/809929974
 
3.7%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
1.9%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
1.9%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
1.9%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
1.9%
https://www.tytnetwork.com2
 
1.9%
https://www.iqiyi.com/a_19rrhskr95.html2
 
1.9%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
1.9%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
1.9%
Other values (55)56
51.9%

Most occurring characters

ValueCountFrequency (%)
/432
 
7.9%
t403
 
7.4%
s344
 
6.3%
w279
 
5.1%
o268
 
4.9%
.257
 
4.7%
e229
 
4.2%
h198
 
3.6%
p181
 
3.3%
c181
 
3.3%
Other values (64)2673
49.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3683
67.6%
Other Punctuation880
 
16.2%
Decimal Number433
 
8.0%
Uppercase Letter296
 
5.4%
Dash Punctuation104
 
1.9%
Math Symbol30
 
0.6%
Connector Punctuation19
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t403
 
10.9%
s344
 
9.3%
w279
 
7.6%
o268
 
7.3%
e229
 
6.2%
h198
 
5.4%
p181
 
4.9%
c181
 
4.9%
a174
 
4.7%
r164
 
4.5%
Other values (16)1262
34.3%
Uppercase Letter
ValueCountFrequency (%)
E33
 
11.1%
P20
 
6.8%
C18
 
6.1%
A17
 
5.7%
N16
 
5.4%
F15
 
5.1%
L15
 
5.1%
W14
 
4.7%
B13
 
4.4%
T12
 
4.1%
Other values (16)123
41.6%
Decimal Number
ValueCountFrequency (%)
082
18.9%
981
18.7%
441
9.5%
840
9.2%
139
9.0%
238
8.8%
531
 
7.2%
727
 
6.2%
327
 
6.2%
627
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/432
49.1%
.257
29.2%
:108
 
12.3%
%57
 
6.5%
?17
 
1.9%
&7
 
0.8%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=28
93.3%
+2
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
-104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3979
73.1%
Common1466
 
26.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t403
 
10.1%
s344
 
8.6%
w279
 
7.0%
o268
 
6.7%
e229
 
5.8%
h198
 
5.0%
p181
 
4.5%
c181
 
4.5%
a174
 
4.4%
r164
 
4.1%
Other values (42)1558
39.2%
Common
ValueCountFrequency (%)
/432
29.5%
.257
17.5%
:108
 
7.4%
-104
 
7.1%
082
 
5.6%
981
 
5.5%
%57
 
3.9%
441
 
2.8%
840
 
2.7%
139
 
2.7%
Other values (12)225
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII5445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/432
 
7.9%
t403
 
7.4%
s344
 
6.3%
w279
 
5.1%
o268
 
4.9%
.257
 
4.7%
e229
 
4.2%
h198
 
3.6%
p181
 
3.3%
c181
 
3.3%
Other values (64)2673
49.1%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
90 
20:00
11 
10:00
 
2
20:40
 
2
23:45
 
1
Other values (8)
 
8

Length

Max length5
Median length0
Mean length1.052631579
Min length0

Characters and Unicode

Total characters120
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)7.9%

Sample

1st row
2nd row
3rd row
4th row23:45
5th row10:00

Common Values

ValueCountFrequency (%)
90
78.9%
20:0011
 
9.6%
10:002
 
1.8%
20:402
 
1.8%
23:451
 
0.9%
08:001
 
0.9%
17:001
 
0.9%
06:001
 
0.9%
17:351
 
0.9%
19:001
 
0.9%
Other values (3)3
 
2.6%

Length

2022-09-04T23:40:06.579101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0011
45.8%
10:002
 
8.3%
20:402
 
8.3%
23:451
 
4.2%
08:001
 
4.2%
17:001
 
4.2%
06:001
 
4.2%
17:351
 
4.2%
19:001
 
4.2%
22:001
 
4.2%
Other values (2)2
 
8.3%

Most occurring characters

ValueCountFrequency (%)
059
49.2%
:24
20.0%
217
 
14.2%
16
 
5.0%
54
 
3.3%
43
 
2.5%
32
 
1.7%
72
 
1.7%
81
 
0.8%
61
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number96
80.0%
Other Punctuation24
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
059
61.5%
217
 
17.7%
16
 
6.2%
54
 
4.2%
43
 
3.1%
32
 
2.1%
72
 
2.1%
81
 
1.0%
61
 
1.0%
91
 
1.0%
Other Punctuation
ValueCountFrequency (%)
:24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
059
49.2%
:24
20.0%
217
 
14.2%
16
 
5.0%
54
 
3.3%
43
 
2.5%
32
 
1.7%
72
 
1.7%
81
 
0.8%
61
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
059
49.2%
:24
20.0%
217
 
14.2%
16
 
5.0%
54
 
3.3%
43
 
2.5%
32
 
1.7%
72
 
1.7%
81
 
0.8%
61
 
0.8%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)57.1%
Missing107
Missing (%)93.9%
Memory size1.0 KiB
6.0
5.3
5.8
5.6

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)42.9%

Sample

1st row5.3
2nd row6.0
3rd row6.0
4th row6.0
5th row6.0

Common Values

ValueCountFrequency (%)
6.04
 
3.5%
5.31
 
0.9%
5.81
 
0.9%
5.61
 
0.9%
(Missing)107
93.9%

Length

2022-09-04T23:40:06.650100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:06.734398image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
6.04
57.1%
5.31
 
14.3%
5.81
 
14.3%
5.61
 
14.3%

Most occurring characters

ValueCountFrequency (%)
.7
33.3%
65
23.8%
04
19.0%
53
14.3%
31
 
4.8%
81
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number14
66.7%
Other Punctuation7
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
65
35.7%
04
28.6%
53
21.4%
31
 
7.1%
81
 
7.1%
Other Punctuation
ValueCountFrequency (%)
.7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.7
33.3%
65
23.8%
04
19.0%
53
14.3%
31
 
4.8%
81
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.7
33.3%
65
23.8%
04
19.0%
53
14.3%
31
 
4.8%
81
 
4.8%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct45
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.61403509
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:06.813303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.3
Q124.25
median37
Q337
95-th percentile75.15
Maximum93
Range92
Interquartile range (IQR)12.75

Descriptive statistics

Standard deviation18.11639299
Coefficient of variation (CV)0.523382869
Kurtosis1.854820291
Mean34.61403509
Median Absolute Deviation (MAD)7
Skewness1.001399575
Sum3946
Variance328.2036951
MonotonicityNot monotonic
2022-09-04T23:40:06.902312image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
3735
30.7%
276
 
5.3%
305
 
4.4%
425
 
4.4%
603
 
2.6%
243
 
2.6%
213
 
2.6%
343
 
2.6%
142
 
1.8%
222
 
1.8%
Other values (35)47
41.2%
ValueCountFrequency (%)
11
0.9%
21
0.9%
32
1.8%
42
1.8%
61
0.9%
91
0.9%
111
0.9%
131
0.9%
142
1.8%
152
1.8%
ValueCountFrequency (%)
931
 
0.9%
901
 
0.9%
841
 
0.9%
822
1.8%
811
 
0.9%
721
 
0.9%
681
 
0.9%
651
 
0.9%
611
 
0.9%
603
2.6%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing114
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct33
Distinct (%)30.0%
Missing4
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean142.4727273
Minimum1
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:06.984878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q121
median126.5
Q3173
95-th percentile380.1
Maximum516
Range515
Interquartile range (IQR)152

Descriptive statistics

Standard deviation120.6010718
Coefficient of variation (CV)0.8464853175
Kurtosis1.540651985
Mean142.4727273
Median Absolute Deviation (MAD)67.5
Skewness1.196019654
Sum15672
Variance14544.61852
MonotonicityNot monotonic
2022-09-04T23:40:07.059947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
17333
28.9%
2127
23.7%
10410
 
8.8%
14
 
3.5%
1184
 
3.5%
3042
 
1.8%
2022
 
1.8%
3272
 
1.8%
672
 
1.8%
1191
 
0.9%
Other values (23)23
20.2%
(Missing)4
 
3.5%
ValueCountFrequency (%)
14
 
3.5%
21
 
0.9%
2127
23.7%
301
 
0.9%
511
 
0.9%
672
 
1.8%
731
 
0.9%
991
 
0.9%
1021
 
0.9%
10410
 
8.8%
ValueCountFrequency (%)
5161
0.9%
5071
0.9%
5061
0.9%
4981
0.9%
4521
0.9%
3811
0.9%
3791
0.9%
3272
1.8%
3191
0.9%
3111
0.9%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)30.0%
Missing4
Missing (%)3.5%
Memory size1.0 KiB
discovery+
33 
YouTube
27 
Tencent QQ
10 
Netflix
Youku
Other values (28)
32 

Length

Max length14
Median length13
Mean length8.227272727
Min length3

Characters and Unicode

Total characters905
Distinct characters56
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)21.8%

Sample

1st rowV LIVE
2nd rowStart
3rd rowYouTube
4th rowКиноПоиск HD
5th rowBilibili

Common Values

ValueCountFrequency (%)
discovery+33
28.9%
YouTube27
23.7%
Tencent QQ10
 
8.8%
Netflix4
 
3.5%
Youku4
 
3.5%
twitch2
 
1.8%
Facebook Watch2
 
1.8%
TV 2 Play2
 
1.8%
iQIYI2
 
1.8%
FOD1
 
0.9%
Other values (23)23
20.2%
(Missing)4
 
3.5%

Length

2022-09-04T23:40:07.133961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
discovery33
25.0%
youtube27
20.5%
tencent10
 
7.6%
qq10
 
7.6%
netflix4
 
3.0%
youku4
 
3.0%
tv3
 
2.3%
facebook2
 
1.5%
watch2
 
1.5%
22
 
1.5%
Other values (32)35
26.5%

Most occurring characters

ValueCountFrequency (%)
e95
 
10.5%
o78
 
8.6%
u70
 
7.7%
i53
 
5.9%
c51
 
5.6%
T45
 
5.0%
d38
 
4.2%
s37
 
4.1%
r37
 
4.1%
y37
 
4.1%
Other values (46)364
40.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter684
75.6%
Uppercase Letter160
 
17.7%
Math Symbol33
 
3.6%
Space Separator22
 
2.4%
Other Punctuation4
 
0.4%
Decimal Number2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e95
13.9%
o78
11.4%
u70
10.2%
i53
 
7.7%
c51
 
7.5%
d38
 
5.6%
s37
 
5.4%
r37
 
5.4%
y37
 
5.4%
v34
 
5.0%
Other values (18)154
22.5%
Uppercase Letter
ValueCountFrequency (%)
T45
28.1%
Y33
20.6%
Q22
13.8%
V10
 
6.2%
N6
 
3.8%
D5
 
3.1%
F5
 
3.1%
I5
 
3.1%
C4
 
2.5%
S4
 
2.5%
Other values (13)21
13.1%
Other Punctuation
ValueCountFrequency (%)
.3
75.0%
:1
 
25.0%
Math Symbol
ValueCountFrequency (%)
+33
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin835
92.3%
Common61
 
6.7%
Cyrillic9
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e95
 
11.4%
o78
 
9.3%
u70
 
8.4%
i53
 
6.3%
c51
 
6.1%
T45
 
5.4%
d38
 
4.6%
s37
 
4.4%
r37
 
4.4%
y37
 
4.4%
Other values (34)294
35.2%
Cyrillic
ValueCountFrequency (%)
и2
22.2%
о2
22.2%
с1
11.1%
П1
11.1%
н1
11.1%
К1
11.1%
к1
11.1%
Common
ValueCountFrequency (%)
+33
54.1%
22
36.1%
.3
 
4.9%
22
 
3.3%
:1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII896
99.0%
Cyrillic9
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e95
 
10.6%
o78
 
8.7%
u70
 
7.8%
i53
 
5.9%
c51
 
5.7%
T45
 
5.0%
d38
 
4.2%
s37
 
4.1%
r37
 
4.1%
y37
 
4.1%
Other values (39)355
39.6%
Cyrillic
ValueCountFrequency (%)
и2
22.2%
о2
22.2%
с1
11.1%
П1
11.1%
н1
11.1%
К1
11.1%
к1
11.1%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)31.4%
Missing79
Missing (%)69.3%
Memory size1.0 KiB
China
15 
United States
Russian Federation
Norway
Korea, Republic of
Other values (6)

Length

Max length25
Median length18
Mean length9.285714286
Min length5

Characters and Unicode

Total characters325
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)17.1%

Sample

1st rowKorea, Republic of
2nd rowRussian Federation
3rd rowRussian Federation
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China15
 
13.2%
United States5
 
4.4%
Russian Federation4
 
3.5%
Norway3
 
2.6%
Korea, Republic of2
 
1.8%
Iran, Islamic Republic of1
 
0.9%
Kazakhstan1
 
0.9%
Turkey1
 
0.9%
Germany1
 
0.9%
Brazil1
 
0.9%
(Missing)79
69.3%

Length

2022-09-04T23:40:07.212902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china15
29.4%
united5
 
9.8%
states5
 
9.8%
russian4
 
7.8%
federation4
 
7.8%
norway3
 
5.9%
republic3
 
5.9%
of3
 
5.9%
korea2
 
3.9%
iran1
 
2.0%
Other values (6)6
 
11.8%

Most occurring characters

ValueCountFrequency (%)
a42
12.9%
i33
 
10.2%
n32
 
9.8%
e25
 
7.7%
t20
 
6.2%
16
 
4.9%
h16
 
4.9%
C15
 
4.6%
s15
 
4.6%
r13
 
4.0%
Other values (25)98
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter258
79.4%
Uppercase Letter48
 
14.8%
Space Separator16
 
4.9%
Other Punctuation3
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a42
16.3%
i33
12.8%
n32
12.4%
e25
9.7%
t20
7.8%
h16
 
6.2%
s15
 
5.8%
r13
 
5.0%
o12
 
4.7%
d9
 
3.5%
Other values (11)41
15.9%
Uppercase Letter
ValueCountFrequency (%)
C15
31.2%
R7
14.6%
S5
 
10.4%
U5
 
10.4%
F4
 
8.3%
N3
 
6.2%
K3
 
6.2%
I2
 
4.2%
T1
 
2.1%
G1
 
2.1%
Other values (2)2
 
4.2%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin306
94.2%
Common19
 
5.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a42
13.7%
i33
 
10.8%
n32
 
10.5%
e25
 
8.2%
t20
 
6.5%
h16
 
5.2%
C15
 
4.9%
s15
 
4.9%
r13
 
4.2%
o12
 
3.9%
Other values (23)83
27.1%
Common
ValueCountFrequency (%)
16
84.2%
,3
 
15.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a42
12.9%
i33
 
10.2%
n32
 
9.8%
e25
 
7.7%
t20
 
6.2%
16
 
4.9%
h16
 
4.9%
C15
 
4.6%
s15
 
4.6%
r13
 
4.0%
Other values (25)98
30.2%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)31.4%
Missing79
Missing (%)69.3%
Memory size1.0 KiB
CN
15 
US
RU
NO
KR
Other values (6)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters70
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)17.1%

Sample

1st rowKR
2nd rowRU
3rd rowRU
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN15
 
13.2%
US5
 
4.4%
RU4
 
3.5%
NO3
 
2.6%
KR2
 
1.8%
IR1
 
0.9%
KZ1
 
0.9%
TR1
 
0.9%
DE1
 
0.9%
BR1
 
0.9%
(Missing)79
69.3%

Length

2022-09-04T23:40:07.289893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn15
42.9%
us5
 
14.3%
ru4
 
11.4%
no3
 
8.6%
kr2
 
5.7%
ir1
 
2.9%
kz1
 
2.9%
tr1
 
2.9%
de1
 
2.9%
br1
 
2.9%

Most occurring characters

ValueCountFrequency (%)
N18
25.7%
C15
21.4%
U9
12.9%
R9
12.9%
S5
 
7.1%
O3
 
4.3%
K3
 
4.3%
I1
 
1.4%
Z1
 
1.4%
T1
 
1.4%
Other values (5)5
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter70
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N18
25.7%
C15
21.4%
U9
12.9%
R9
12.9%
S5
 
7.1%
O3
 
4.3%
K3
 
4.3%
I1
 
1.4%
Z1
 
1.4%
T1
 
1.4%
Other values (5)5
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Latin70
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N18
25.7%
C15
21.4%
U9
12.9%
R9
12.9%
S5
 
7.1%
O3
 
4.3%
K3
 
4.3%
I1
 
1.4%
Z1
 
1.4%
T1
 
1.4%
Other values (5)5
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N18
25.7%
C15
21.4%
U9
12.9%
R9
12.9%
S5
 
7.1%
O3
 
4.3%
K3
 
4.3%
I1
 
1.4%
Z1
 
1.4%
T1
 
1.4%
Other values (5)5
 
7.1%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)31.4%
Missing79
Missing (%)69.3%
Memory size1.0 KiB
Asia/Shanghai
15 
America/New_York
Asia/Kamchatka
Europe/Oslo
Asia/Seoul
Other values (6)

Length

Max length16
Median length15
Mean length13.25714286
Min length10

Characters and Unicode

Total characters464
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)17.1%

Sample

1st rowAsia/Seoul
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai15
 
13.2%
America/New_York5
 
4.4%
Asia/Kamchatka4
 
3.5%
Europe/Oslo3
 
2.6%
Asia/Seoul2
 
1.8%
Asia/Tehran1
 
0.9%
Asia/Qyzylorda1
 
0.9%
Europe/Istanbul1
 
0.9%
Europe/Busingen1
 
0.9%
America/Noronha1
 
0.9%
(Missing)79
69.3%

Length

2022-09-04T23:40:07.364895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai15
42.9%
america/new_york5
 
14.3%
asia/kamchatka4
 
11.4%
europe/oslo3
 
8.6%
asia/seoul2
 
5.7%
asia/tehran1
 
2.9%
asia/qyzylorda1
 
2.9%
europe/istanbul1
 
2.9%
europe/busingen1
 
2.9%
america/noronha1
 
2.9%

Most occurring characters

ValueCountFrequency (%)
a76
16.4%
i46
 
9.9%
h36
 
7.8%
/35
 
7.5%
A30
 
6.5%
s29
 
6.2%
e20
 
4.3%
o20
 
4.3%
n20
 
4.3%
r19
 
4.1%
Other values (24)133
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter349
75.2%
Uppercase Letter75
 
16.2%
Other Punctuation35
 
7.5%
Connector Punctuation5
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a76
21.8%
i46
13.2%
h36
10.3%
s29
 
8.3%
e20
 
5.7%
o20
 
5.7%
n20
 
5.7%
r19
 
5.4%
g16
 
4.6%
c10
 
2.9%
Other values (11)57
16.3%
Uppercase Letter
ValueCountFrequency (%)
A30
40.0%
S17
22.7%
N6
 
8.0%
E5
 
6.7%
Y5
 
6.7%
K4
 
5.3%
O3
 
4.0%
T2
 
2.7%
Q1
 
1.3%
I1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/35
100.0%
Connector Punctuation
ValueCountFrequency (%)
_5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin424
91.4%
Common40
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a76
17.9%
i46
10.8%
h36
 
8.5%
A30
 
7.1%
s29
 
6.8%
e20
 
4.7%
o20
 
4.7%
n20
 
4.7%
r19
 
4.5%
S17
 
4.0%
Other values (22)111
26.2%
Common
ValueCountFrequency (%)
/35
87.5%
_5
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a76
16.4%
i46
 
9.9%
h36
 
7.8%
/35
 
7.5%
A30
 
6.5%
s29
 
6.2%
e20
 
4.3%
o20
 
4.3%
n20
 
4.3%
r19
 
4.1%
Other values (24)133
28.7%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)11.2%
Missing34
Missing (%)29.8%
Memory size1.0 KiB
https://www.discoveryplus.com/
33 
https://www.youtube.com
27 
https://v.qq.com/
10 
https://www.netflix.com/
https://www.iq.com/
 
2
Other values (4)

Length

Max length30
Median length25
Mean length25.075
Min length17

Characters and Unicode

Total characters2006
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)5.0%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://www.youtube.com
3rd rowhttps://hd.kinopoisk.ru/
4th rowhttps://v.qq.com/
5th rowhttps://tv.naver.com/

Common Values

ValueCountFrequency (%)
https://www.discoveryplus.com/33
28.9%
https://www.youtube.com27
23.7%
https://v.qq.com/10
 
8.8%
https://www.netflix.com/4
 
3.5%
https://www.iq.com/2
 
1.8%
https://www.vlive.tv/home1
 
0.9%
https://hd.kinopoisk.ru/1
 
0.9%
https://tv.naver.com/1
 
0.9%
https://www.hulu.com/1
 
0.9%
(Missing)34
29.8%

Length

2022-09-04T23:40:07.443901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:07.539353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.discoveryplus.com33
41.2%
https://www.youtube.com27
33.8%
https://v.qq.com10
 
12.5%
https://www.netflix.com4
 
5.0%
https://www.iq.com2
 
2.5%
https://www.vlive.tv/home1
 
1.2%
https://hd.kinopoisk.ru1
 
1.2%
https://tv.naver.com1
 
1.2%
https://www.hulu.com1
 
1.2%

Most occurring characters

ValueCountFrequency (%)
/213
 
10.6%
w204
 
10.2%
t193
 
9.6%
.160
 
8.0%
s147
 
7.3%
o141
 
7.0%
p114
 
5.7%
c111
 
5.5%
u90
 
4.5%
h83
 
4.1%
Other values (16)550
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1553
77.4%
Other Punctuation453
 
22.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w204
13.1%
t193
12.4%
s147
9.5%
o141
9.1%
p114
 
7.3%
c111
 
7.1%
u90
 
5.8%
h83
 
5.3%
m79
 
5.1%
e67
 
4.3%
Other values (13)324
20.9%
Other Punctuation
ValueCountFrequency (%)
/213
47.0%
.160
35.3%
:80
 
17.7%

Most occurring scripts

ValueCountFrequency (%)
Latin1553
77.4%
Common453
 
22.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w204
13.1%
t193
12.4%
s147
9.5%
o141
9.1%
p114
 
7.3%
c111
 
7.1%
u90
 
5.8%
h83
 
5.3%
m79
 
5.1%
e67
 
4.3%
Other values (13)324
20.9%
Common
ValueCountFrequency (%)
/213
47.0%
.160
35.3%
:80
 
17.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII2006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/213
 
10.6%
w204
 
10.2%
t193
 
9.6%
.160
 
8.0%
s147
 
7.3%
o141
 
7.0%
p114
 
5.7%
c111
 
5.5%
u90
 
4.5%
h83
 
4.1%
Other values (16)550
27.4%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing114
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing113
Missing (%)99.1%
Memory size1.0 KiB
19056.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row19056.0

Common Values

ValueCountFrequency (%)
19056.01
 
0.9%
(Missing)113
99.1%

Length

2022-09-04T23:40:07.641250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:07.718862image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
19056.01
100.0%

Most occurring characters

ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
85.7%
Other Punctuation1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02
33.3%
11
16.7%
91
16.7%
51
16.7%
61
16.7%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct45
Distinct (%)83.3%
Missing60
Missing (%)52.6%
Infinite0
Infinite (%)0.0%
Mean349355.7963
Minimum104271
Maximum397247
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:07.791660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile267211.25
Q1322763.5
median370179.5
Q3391319
95-th percentile393613.4
Maximum397247
Range292976
Interquartile range (IQR)68555.5

Descriptive statistics

Standard deviation55889.32717
Coefficient of variation (CV)0.159978245
Kurtosis5.505606751
Mean349355.7963
Median Absolute Deviation (MAD)22372.5
Skewness-1.937466738
Sum18865213
Variance3123616891
MonotonicityNot monotonic
2022-09-04T23:40:07.875808image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
3885874
 
3.5%
3922142
 
1.8%
3923622
 
1.8%
3933812
 
1.8%
2787932
 
1.8%
2813452
 
1.8%
3972472
 
1.8%
3583891
 
0.9%
3524401
 
0.9%
3931741
 
0.9%
Other values (35)35
30.7%
(Missing)60
52.6%
ValueCountFrequency (%)
1042711
0.9%
2604361
0.9%
2651931
0.9%
2682981
0.9%
2743991
0.9%
2787932
1.8%
2813452
1.8%
2840461
0.9%
2879531
0.9%
2906861
0.9%
ValueCountFrequency (%)
3972472
1.8%
3940451
0.9%
3933812
1.8%
3931741
0.9%
3926491
0.9%
3924551
0.9%
3923622
1.8%
3922381
0.9%
3922142
1.8%
3915681
0.9%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct33
Distinct (%)82.5%
Missing74
Missing (%)64.9%
Memory size1.0 KiB
tt13110256
tt1714810
 
2
tt13598988
 
2
tt13539710
 
2
tt10094402
 
2
Other values (28)
28 

Length

Max length10
Median length10
Mean length9.6
Min length9

Characters and Unicode

Total characters384
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)70.0%

Sample

1st rowtt11105888
2nd rowtt15127174
3rd rowtt11492320
4th rowtt11450050
5th rowtt10727044

Common Values

ValueCountFrequency (%)
tt131102564
 
3.5%
tt17148102
 
1.8%
tt135989882
 
1.8%
tt135397102
 
1.8%
tt100944022
 
1.8%
tt49071781
 
0.9%
tt26102601
 
0.9%
tt00965971
 
0.9%
tt132805421
 
0.9%
tt106806141
 
0.9%
Other values (23)23
 
20.2%
(Missing)74
64.9%

Length

2022-09-04T23:40:07.958733image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt131102564
 
10.0%
tt135989882
 
5.0%
tt135397102
 
5.0%
tt100944022
 
5.0%
tt17148102
 
5.0%
tt66189221
 
2.5%
tt114500501
 
2.5%
tt111058881
 
2.5%
tt110924821
 
2.5%
tt122398241
 
2.5%
Other values (23)23
57.5%

Most occurring characters

ValueCountFrequency (%)
t80
20.8%
161
15.9%
043
11.2%
836
9.4%
234
8.9%
324
 
6.2%
424
 
6.2%
523
 
6.0%
921
 
5.5%
620
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number304
79.2%
Lowercase Letter80
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
161
20.1%
043
14.1%
836
11.8%
234
11.2%
324
 
7.9%
424
 
7.9%
523
 
7.6%
921
 
6.9%
620
 
6.6%
718
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
t80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common304
79.2%
Latin80
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
161
20.1%
043
14.1%
836
11.8%
234
11.2%
324
 
7.9%
424
 
7.9%
523
 
7.6%
921
 
6.9%
620
 
6.6%
718
 
5.9%
Latin
ValueCountFrequency (%)
t80
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t80
20.8%
161
15.9%
043
11.2%
836
9.4%
234
8.9%
324
 
6.2%
424
 
6.2%
523
 
6.0%
921
 
5.5%
620
 
5.2%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)61.3%
Missing3
Missing (%)2.6%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/317/794301.jpg
32 
https://static.tvmaze.com/uploads/images/medium_portrait/274/687129.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg
 
2
Other values (63)
69 

Length

Max length72
Median length71
Mean length70.97297297
Min length70

Characters and Unicode

Total characters7878
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)51.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/278/695317.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/317/794301.jpg32
28.1%
https://static.tvmaze.com/uploads/images/medium_portrait/274/687129.jpg4
 
3.5%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
1.8%
Other values (58)59
51.8%
(Missing)3
 
2.6%

Length

2022-09-04T23:40:08.141278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/317/794301.jpg32
28.8%
https://static.tvmaze.com/uploads/images/medium_portrait/274/687129.jpg4
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg2
 
1.8%
Other values (58)59
53.2%

Most occurring characters

ValueCountFrequency (%)
t777
 
9.9%
/777
 
9.9%
m555
 
7.0%
a555
 
7.0%
p444
 
5.6%
s444
 
5.6%
i444
 
5.6%
o333
 
4.2%
.333
 
4.2%
e333
 
4.2%
Other values (22)2883
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5550
70.4%
Other Punctuation1221
 
15.5%
Decimal Number996
 
12.6%
Connector Punctuation111
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t777
14.0%
m555
10.0%
a555
10.0%
p444
 
8.0%
s444
 
8.0%
i444
 
8.0%
o333
 
6.0%
e333
 
6.0%
u222
 
4.0%
c222
 
4.0%
Other values (8)1221
22.0%
Decimal Number
ValueCountFrequency (%)
7148
14.9%
1142
14.3%
3137
13.8%
995
9.5%
492
9.2%
890
9.0%
088
8.8%
279
7.9%
569
6.9%
656
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/777
63.6%
.333
27.3%
:111
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5550
70.4%
Common2328
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t777
14.0%
m555
10.0%
a555
10.0%
p444
 
8.0%
s444
 
8.0%
i444
 
8.0%
o333
 
6.0%
e333
 
6.0%
u222
 
4.0%
c222
 
4.0%
Other values (8)1221
22.0%
Common
ValueCountFrequency (%)
/777
33.4%
.333
14.3%
7148
 
6.4%
1142
 
6.1%
3137
 
5.9%
_111
 
4.8%
:111
 
4.8%
995
 
4.1%
492
 
4.0%
890
 
3.9%
Other values (4)292
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII7878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t777
 
9.9%
/777
 
9.9%
m555
 
7.0%
a555
 
7.0%
p444
 
5.6%
s444
 
5.6%
i444
 
5.6%
o333
 
4.2%
.333
 
4.2%
e333
 
4.2%
Other values (22)2883
36.6%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)61.3%
Missing3
Missing (%)2.6%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/317/794301.jpg
32 
https://static.tvmaze.com/uploads/images/original_untouched/274/687129.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg
 
2
Other values (63)
69 

Length

Max length75
Median length74
Mean length73.97297297
Min length73

Characters and Unicode

Total characters8211
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)51.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/278/695317.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/317/794301.jpg32
28.1%
https://static.tvmaze.com/uploads/images/original_untouched/274/687129.jpg4
 
3.5%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
1.8%
Other values (58)59
51.8%
(Missing)3
 
2.6%

Length

2022-09-04T23:40:08.219461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/317/794301.jpg32
28.8%
https://static.tvmaze.com/uploads/images/original_untouched/274/687129.jpg4
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg2
 
1.8%
Other values (58)59
53.2%

Most occurring characters

ValueCountFrequency (%)
/777
 
9.5%
t666
 
8.1%
a555
 
6.8%
s444
 
5.4%
i444
 
5.4%
o444
 
5.4%
p333
 
4.1%
c333
 
4.1%
.333
 
4.1%
g333
 
4.1%
Other values (23)3549
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5883
71.6%
Other Punctuation1221
 
14.9%
Decimal Number996
 
12.1%
Connector Punctuation111
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t666
 
11.3%
a555
 
9.4%
s444
 
7.5%
i444
 
7.5%
o444
 
7.5%
p333
 
5.7%
c333
 
5.7%
g333
 
5.7%
m333
 
5.7%
e333
 
5.7%
Other values (9)1665
28.3%
Decimal Number
ValueCountFrequency (%)
7148
14.9%
1142
14.3%
3137
13.8%
995
9.5%
492
9.2%
890
9.0%
088
8.8%
279
7.9%
569
6.9%
656
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/777
63.6%
.333
27.3%
:111
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5883
71.6%
Common2328
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t666
 
11.3%
a555
 
9.4%
s444
 
7.5%
i444
 
7.5%
o444
 
7.5%
p333
 
5.7%
c333
 
5.7%
g333
 
5.7%
m333
 
5.7%
e333
 
5.7%
Other values (9)1665
28.3%
Common
ValueCountFrequency (%)
/777
33.4%
.333
14.3%
7148
 
6.4%
1142
 
6.1%
3137
 
5.9%
:111
 
4.8%
_111
 
4.8%
995
 
4.1%
492
 
4.0%
890
 
3.9%
Other values (4)292
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII8211
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/777
 
9.5%
t666
 
8.1%
a555
 
6.8%
s444
 
5.4%
i444
 
5.4%
o444
 
5.4%
p333
 
4.1%
c333
 
4.1%
.333
 
4.1%
g333
 
4.1%
Other values (23)3549
43.2%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)59.4%
Missing8
Missing (%)7.0%
Memory size1.0 KiB
<p>Relive some of the memorable moments our couples have faced on their journeys so far. From whopping age gaps to complex language barriers, explore their ups and downs as they prepared to embark on their new lives together.</p>
32 
<p><b>Song Exploder</b>, based on the hit podcast, spotlights some of the world's greatest musicians as they reveal how they brought one of their songs to life.</p>
 
4
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>
 
2
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>
 
2
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>
 
2
Other values (58)
64 

Length

Max length1483
Median length541
Mean length309.8490566
Min length39

Characters and Unicode

Total characters32844
Distinct characters86
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)49.1%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>
3rd row<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>
4th row<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>
5th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>

Common Values

ValueCountFrequency (%)
<p>Relive some of the memorable moments our couples have faced on their journeys so far. From whopping age gaps to complex language barriers, explore their ups and downs as they prepared to embark on their new lives together.</p>32
28.1%
<p><b>Song Exploder</b>, based on the hit podcast, spotlights some of the world's greatest musicians as they reveal how they brought one of their songs to life.</p>4
 
3.5%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
1.8%
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>2
 
1.8%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
1.8%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
1.8%
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>2
 
1.8%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>2
 
1.8%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
1.8%
<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>2
 
1.8%
Other values (53)54
47.4%
(Missing)8
 
7.0%

Length

2022-09-04T23:40:08.315814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the273
 
5.0%
to178
 
3.3%
and167
 
3.1%
of148
 
2.7%
their127
 
2.3%
a111
 
2.0%
on93
 
1.7%
in70
 
1.3%
as61
 
1.1%
they58
 
1.1%
Other values (1515)4159
76.4%

Most occurring characters

ValueCountFrequency (%)
5327
16.2%
e3381
 
10.3%
o2080
 
6.3%
t1998
 
6.1%
a1905
 
5.8%
r1728
 
5.3%
n1696
 
5.2%
s1669
 
5.1%
i1637
 
5.0%
h1285
 
3.9%
Other values (76)10138
30.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter25150
76.6%
Space Separator5339
 
16.3%
Other Punctuation862
 
2.6%
Uppercase Letter798
 
2.4%
Math Symbol598
 
1.8%
Dash Punctuation45
 
0.1%
Decimal Number45
 
0.1%
Close Punctuation3
 
< 0.1%
Open Punctuation3
 
< 0.1%
Currency Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3381
13.4%
o2080
 
8.3%
t1998
 
7.9%
a1905
 
7.6%
r1728
 
6.9%
n1696
 
6.7%
s1669
 
6.6%
i1637
 
6.5%
h1285
 
5.1%
l974
 
3.9%
Other values (21)6797
27.0%
Uppercase Letter
ValueCountFrequency (%)
T93
 
11.7%
A62
 
7.8%
S59
 
7.4%
F57
 
7.1%
R52
 
6.5%
C43
 
5.4%
Y40
 
5.0%
H39
 
4.9%
J35
 
4.4%
M34
 
4.3%
Other values (17)284
35.6%
Other Punctuation
ValueCountFrequency (%)
,308
35.7%
.275
31.9%
/156
18.1%
'61
 
7.1%
"24
 
2.8%
:14
 
1.6%
!12
 
1.4%
?7
 
0.8%
;3
 
0.3%
2
 
0.2%
Decimal Number
ValueCountFrequency (%)
014
31.1%
110
22.2%
210
22.2%
53
 
6.7%
72
 
4.4%
32
 
4.4%
82
 
4.4%
42
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
-34
75.6%
9
 
20.0%
2
 
4.4%
Space Separator
ValueCountFrequency (%)
5327
99.8%
 12
 
0.2%
Math Symbol
ValueCountFrequency (%)
>299
50.0%
<299
50.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin25948
79.0%
Common6896
 
21.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3381
13.0%
o2080
 
8.0%
t1998
 
7.7%
a1905
 
7.3%
r1728
 
6.7%
n1696
 
6.5%
s1669
 
6.4%
i1637
 
6.3%
h1285
 
5.0%
l974
 
3.8%
Other values (48)7595
29.3%
Common
ValueCountFrequency (%)
5327
77.2%
,308
 
4.5%
>299
 
4.3%
<299
 
4.3%
.275
 
4.0%
/156
 
2.3%
'61
 
0.9%
-34
 
0.5%
"24
 
0.3%
014
 
0.2%
Other values (18)99
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32811
99.9%
None20
 
0.1%
Punctuation13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5327
16.2%
e3381
 
10.3%
o2080
 
6.3%
t1998
 
6.1%
a1905
 
5.8%
r1728
 
5.3%
n1696
 
5.2%
s1669
 
5.1%
i1637
 
5.0%
h1285
 
3.9%
Other values (66)10105
30.8%
None
ValueCountFrequency (%)
 12
60.0%
ö2
 
10.0%
ü2
 
10.0%
Ç1
 
5.0%
ş1
 
5.0%
å1
 
5.0%
é1
 
5.0%
Punctuation
ValueCountFrequency (%)
9
69.2%
2
 
15.4%
2
 
15.4%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct71
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1640531154
Minimum1604587119
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:08.412180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1604587119
5-th percentile1608887256
Q11640112415
median1640112415
Q31653280329
95-th percentile1661874261
Maximum1662346277
Range57759158
Interquartile range (IQR)13167914.25

Descriptive statistics

Standard deviation16465264.57
Coefficient of variation (CV)0.01003654489
Kurtosis-0.3510812093
Mean1640531154
Median Absolute Deviation (MAD)9862755
Skewness-0.7428591583
Sum1.870205516 × 1011
Variance2.711049375 × 1014
MonotonicityNot monotonic
2022-09-04T23:40:08.502559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
164011241532
28.1%
16088872564
 
3.5%
16508264802
 
1.8%
16124781452
 
1.8%
16128425832
 
1.8%
16184666822
 
1.8%
16090607262
 
1.8%
16544453122
 
1.8%
16095351412
 
1.8%
16446505822
 
1.8%
Other values (61)62
54.4%
ValueCountFrequency (%)
16045871191
 
0.9%
16083529671
 
0.9%
16084062791
 
0.9%
16084990071
 
0.9%
16088872564
3.5%
16090607262
1.8%
16095351412
1.8%
16113514451
 
0.9%
16114368421
 
0.9%
16124781452
1.8%
ValueCountFrequency (%)
16623462771
0.9%
16622348491
0.9%
16622162831
0.9%
16619744211
0.9%
16619689571
0.9%
16618875351
0.9%
16618671131
0.9%
16617904371
0.9%
16615328091
0.9%
16614758321
0.9%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct71
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/shows/55355
32 
https://api.tvmaze.com/shows/50616
 
4
https://api.tvmaze.com/shows/52108
 
2
https://api.tvmaze.com/shows/52524
 
2
https://api.tvmaze.com/shows/52400
 
2
Other values (66)
72 

Length

Max length34
Median length34
Mean length33.99122807
Min length33

Characters and Unicode

Total characters3875
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)52.6%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/49422
3rd rowhttps://api.tvmaze.com/shows/51065
4th rowhttps://api.tvmaze.com/shows/52933
5th rowhttps://api.tvmaze.com/shows/51336

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/5535532
28.1%
https://api.tvmaze.com/shows/506164
 
3.5%
https://api.tvmaze.com/shows/521082
 
1.8%
https://api.tvmaze.com/shows/525242
 
1.8%
https://api.tvmaze.com/shows/524002
 
1.8%
https://api.tvmaze.com/shows/547622
 
1.8%
https://api.tvmaze.com/shows/521592
 
1.8%
https://api.tvmaze.com/shows/521072
 
1.8%
https://api.tvmaze.com/shows/521042
 
1.8%
https://api.tvmaze.com/shows/501062
 
1.8%
Other values (61)62
54.4%

Length

2022-09-04T23:40:08.584897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/5535532
28.1%
https://api.tvmaze.com/shows/506164
 
3.5%
https://api.tvmaze.com/shows/521592
 
1.8%
https://api.tvmaze.com/shows/152502
 
1.8%
https://api.tvmaze.com/shows/501062
 
1.8%
https://api.tvmaze.com/shows/521072
 
1.8%
https://api.tvmaze.com/shows/521042
 
1.8%
https://api.tvmaze.com/shows/547622
 
1.8%
https://api.tvmaze.com/shows/524002
 
1.8%
https://api.tvmaze.com/shows/525242
 
1.8%
Other values (61)62
54.4%

Most occurring characters

ValueCountFrequency (%)
/456
 
11.8%
s342
 
8.8%
t342
 
8.8%
h228
 
5.9%
p228
 
5.9%
a228
 
5.9%
.228
 
5.9%
o228
 
5.9%
m228
 
5.9%
5197
 
5.1%
Other values (16)1170
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2508
64.7%
Other Punctuation798
 
20.6%
Decimal Number569
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s342
13.6%
t342
13.6%
h228
9.1%
p228
9.1%
a228
9.1%
o228
9.1%
m228
9.1%
e114
 
4.5%
w114
 
4.5%
c114
 
4.5%
Other values (3)342
13.6%
Decimal Number
ValueCountFrequency (%)
5197
34.6%
371
 
12.5%
152
 
9.1%
247
 
8.3%
446
 
8.1%
045
 
7.9%
642
 
7.4%
925
 
4.4%
823
 
4.0%
721
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/456
57.1%
.228
28.6%
:114
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2508
64.7%
Common1367
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/456
33.4%
.228
16.7%
5197
14.4%
:114
 
8.3%
371
 
5.2%
152
 
3.8%
247
 
3.4%
446
 
3.4%
045
 
3.3%
642
 
3.1%
Other values (3)69
 
5.0%
Latin
ValueCountFrequency (%)
s342
13.6%
t342
13.6%
h228
9.1%
p228
9.1%
a228
9.1%
o228
9.1%
m228
9.1%
e114
 
4.5%
w114
 
4.5%
c114
 
4.5%
Other values (3)342
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/456
 
11.8%
s342
 
8.8%
t342
 
8.8%
h228
 
5.9%
p228
 
5.9%
a228
 
5.9%
.228
 
5.9%
o228
 
5.9%
m228
 
5.9%
5197
 
5.1%
Other values (16)1170
30.2%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct71
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/2092988
32 
https://api.tvmaze.com/episodes/1986150
 
4
https://api.tvmaze.com/episodes/1976202
 
2
https://api.tvmaze.com/episodes/1988079
 
2
https://api.tvmaze.com/episodes/1984963
 
2
Other values (66)
72 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4446
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)52.6%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/1954454
3rd rowhttps://api.tvmaze.com/episodes/2007760
4th rowhttps://api.tvmaze.com/episodes/2245512
5th rowhttps://api.tvmaze.com/episodes/1964569

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/209298832
28.1%
https://api.tvmaze.com/episodes/19861504
 
3.5%
https://api.tvmaze.com/episodes/19762022
 
1.8%
https://api.tvmaze.com/episodes/19880792
 
1.8%
https://api.tvmaze.com/episodes/19849632
 
1.8%
https://api.tvmaze.com/episodes/20714942
 
1.8%
https://api.tvmaze.com/episodes/19776512
 
1.8%
https://api.tvmaze.com/episodes/19761662
 
1.8%
https://api.tvmaze.com/episodes/19760542
 
1.8%
https://api.tvmaze.com/episodes/19769342
 
1.8%
Other values (61)62
54.4%

Length

2022-09-04T23:40:08.648893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/209298832
28.1%
https://api.tvmaze.com/episodes/19861504
 
3.5%
https://api.tvmaze.com/episodes/19776512
 
1.8%
https://api.tvmaze.com/episodes/23012762
 
1.8%
https://api.tvmaze.com/episodes/19769342
 
1.8%
https://api.tvmaze.com/episodes/19761662
 
1.8%
https://api.tvmaze.com/episodes/19760542
 
1.8%
https://api.tvmaze.com/episodes/20714942
 
1.8%
https://api.tvmaze.com/episodes/19849632
 
1.8%
https://api.tvmaze.com/episodes/19880792
 
1.8%
Other values (61)62
54.4%

Most occurring characters

ValueCountFrequency (%)
/456
 
10.3%
p342
 
7.7%
s342
 
7.7%
e342
 
7.7%
t342
 
7.7%
o228
 
5.1%
a228
 
5.1%
i228
 
5.1%
.228
 
5.1%
m228
 
5.1%
Other values (16)1482
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2850
64.1%
Other Punctuation798
 
17.9%
Decimal Number798
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p342
12.0%
s342
12.0%
e342
12.0%
t342
12.0%
o228
8.0%
a228
8.0%
i228
8.0%
m228
8.0%
h114
 
4.0%
d114
 
4.0%
Other values (3)342
12.0%
Decimal Number
ValueCountFrequency (%)
2157
19.7%
9132
16.5%
8108
13.5%
080
10.0%
178
9.8%
761
 
7.6%
352
 
6.5%
646
 
5.8%
544
 
5.5%
440
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/456
57.1%
.228
28.6%
:114
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2850
64.1%
Common1596
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/456
28.6%
.228
14.3%
2157
 
9.8%
9132
 
8.3%
:114
 
7.1%
8108
 
6.8%
080
 
5.0%
178
 
4.9%
761
 
3.8%
352
 
3.3%
Other values (3)130
 
8.1%
Latin
ValueCountFrequency (%)
p342
12.0%
s342
12.0%
e342
12.0%
t342
12.0%
o228
8.0%
a228
8.0%
i228
8.0%
m228
8.0%
h114
 
4.0%
d114
 
4.0%
Other values (3)342
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/456
 
10.3%
p342
 
7.7%
s342
 
7.7%
e342
 
7.7%
t342
 
7.7%
o228
 
5.1%
a228
 
5.1%
i228
 
5.1%
.228
 
5.1%
m228
 
5.1%
Other values (16)1482
33.3%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing114
Missing (%)100.0%
Memory size1.0 KiB

image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct55
Distinct (%)100.0%
Missing59
Missing (%)51.8%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/294/737208.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/317/794273.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/317/794274.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/317/794275.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/317/794276.jpg
 
1
Other values (50)
50 

Length

Max length73
Median length72
Mean length72.05454545
Min length72

Characters and Unicode

Total characters3963
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/737208.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726349.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/289/722681.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/735555.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/737208.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794273.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794274.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794275.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794276.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794277.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794278.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794279.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794281.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/317/794282.jpg1
 
0.9%
Other values (45)45
39.5%
(Missing)59
51.8%

Length

2022-09-04T23:40:08.714099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/737208.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/358/896918.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726349.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722681.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721854.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/294/735555.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722726.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/418/1047206.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722711.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722712.jpg1
 
1.8%
Other values (45)45
81.8%

Most occurring characters

ValueCountFrequency (%)
/385
 
9.7%
a330
 
8.3%
s275
 
6.9%
m275
 
6.9%
t275
 
6.9%
p220
 
5.6%
e220
 
5.6%
i165
 
4.2%
c165
 
4.2%
.165
 
4.2%
Other values (22)1488
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2805
70.8%
Other Punctuation605
 
15.3%
Decimal Number498
 
12.6%
Connector Punctuation55
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a330
11.8%
s275
9.8%
m275
9.8%
t275
9.8%
p220
 
7.8%
e220
 
7.8%
i165
 
5.9%
c165
 
5.9%
d165
 
5.9%
l110
 
3.9%
Other values (8)605
21.6%
Decimal Number
ValueCountFrequency (%)
7110
22.1%
282
16.5%
960
12.0%
153
10.6%
448
9.6%
345
9.0%
841
 
8.2%
630
 
6.0%
017
 
3.4%
512
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/385
63.6%
.165
27.3%
:55
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2805
70.8%
Common1158
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a330
11.8%
s275
9.8%
m275
9.8%
t275
9.8%
p220
 
7.8%
e220
 
7.8%
i165
 
5.9%
c165
 
5.9%
d165
 
5.9%
l110
 
3.9%
Other values (8)605
21.6%
Common
ValueCountFrequency (%)
/385
33.2%
.165
14.2%
7110
 
9.5%
282
 
7.1%
960
 
5.2%
_55
 
4.7%
:55
 
4.7%
153
 
4.6%
448
 
4.1%
345
 
3.9%
Other values (4)100
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3963
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/385
 
9.7%
a330
 
8.3%
s275
 
6.9%
m275
 
6.9%
t275
 
6.9%
p220
 
5.6%
e220
 
5.6%
i165
 
4.2%
c165
 
4.2%
.165
 
4.2%
Other values (22)1488
37.5%

image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct55
Distinct (%)100.0%
Missing59
Missing (%)51.8%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/294/737208.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/317/794273.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/317/794274.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/317/794275.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/317/794276.jpg
 
1
Other values (50)
50 

Length

Max length75
Median length74
Mean length74.05454545
Min length74

Characters and Unicode

Total characters4073
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/737208.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726349.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/722681.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721854.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/735555.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/737208.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794273.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794274.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794275.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794276.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794277.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794278.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794279.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794281.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/317/794282.jpg1
 
0.9%
Other values (45)45
39.5%
(Missing)59
51.8%

Length

2022-09-04T23:40:08.782059image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/737208.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/358/896918.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/290/726349.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/722681.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/288/721854.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/294/735555.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/722726.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/418/1047206.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/722711.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/722712.jpg1
 
1.8%
Other values (45)45
81.8%

Most occurring characters

ValueCountFrequency (%)
/385
 
9.5%
t330
 
8.1%
a275
 
6.8%
s220
 
5.4%
o220
 
5.4%
i220
 
5.4%
m165
 
4.1%
u165
 
4.1%
e165
 
4.1%
g165
 
4.1%
Other values (23)1763
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2915
71.6%
Other Punctuation605
 
14.9%
Decimal Number498
 
12.2%
Connector Punctuation55
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t330
 
11.3%
a275
 
9.4%
s220
 
7.5%
o220
 
7.5%
i220
 
7.5%
m165
 
5.7%
u165
 
5.7%
e165
 
5.7%
g165
 
5.7%
c165
 
5.7%
Other values (9)825
28.3%
Decimal Number
ValueCountFrequency (%)
7110
22.1%
282
16.5%
960
12.0%
153
10.6%
448
9.6%
345
9.0%
841
 
8.2%
630
 
6.0%
017
 
3.4%
512
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/385
63.6%
.165
27.3%
:55
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2915
71.6%
Common1158
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t330
 
11.3%
a275
 
9.4%
s220
 
7.5%
o220
 
7.5%
i220
 
7.5%
m165
 
5.7%
u165
 
5.7%
e165
 
5.7%
g165
 
5.7%
c165
 
5.7%
Other values (9)825
28.3%
Common
ValueCountFrequency (%)
/385
33.2%
.165
14.2%
7110
 
9.5%
282
 
7.1%
960
 
5.2%
_55
 
4.7%
:55
 
4.7%
153
 
4.6%
448
 
4.1%
345
 
3.9%
Other values (4)100
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4073
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/385
 
9.5%
t330
 
8.1%
a275
 
6.8%
s220
 
5.4%
o220
 
5.4%
i220
 
5.4%
m165
 
4.1%
u165
 
4.1%
e165
 
4.1%
g165
 
4.1%
Other values (23)1763
43.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)88.9%
Missing105
Missing (%)92.1%
Infinite0
Infinite (%)0.0%
Mean423.5555556
Minimum112
Maximum1354
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-04T23:40:08.850663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum112
5-th percentile118
Q1159
median374
Q3432
95-th percentile1018
Maximum1354
Range1242
Interquartile range (IQR)273

Descriptive statistics

Standard deviation378.2955561
Coefficient of variation (CV)0.8931427086
Kurtosis5.522888489
Mean423.5555556
Median Absolute Deviation (MAD)140
Skewness2.166376939
Sum3812
Variance143107.5278
MonotonicityNot monotonic
2022-09-04T23:40:08.913493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4322
 
1.8%
3081
 
0.9%
5141
 
0.9%
1271
 
0.9%
1591
 
0.9%
3741
 
0.9%
13541
 
0.9%
1121
 
0.9%
(Missing)105
92.1%
ValueCountFrequency (%)
1121
0.9%
1271
0.9%
1591
0.9%
3081
0.9%
3741
0.9%
4322
1.8%
5141
0.9%
13541
0.9%
ValueCountFrequency (%)
13541
0.9%
5141
0.9%
4322
1.8%
3741
0.9%
3081
0.9%
1591
0.9%
1271
0.9%
1121
0.9%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)88.9%
Missing105
Missing (%)92.1%
Memory size1.0 KiB
OCS Max
ТНТ
ТВ-3
SBS
TBS
Other values (3)

Length

Max length11
Median length8
Mean length5.555555556
Min length3

Characters and Unicode

Total characters50
Distinct characters27
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)77.8%

Sample

1st rowТНТ
2nd rowТВ-3
3rd rowSBS
4th rowTBS
5th rowTV Globo

Common Values

ValueCountFrequency (%)
OCS Max2
 
1.8%
ТНТ1
 
0.9%
ТВ-31
 
0.9%
SBS1
 
0.9%
TBS1
 
0.9%
TV Globo1
 
0.9%
Fuji TV TWO1
 
0.9%
RTL41
 
0.9%
(Missing)105
92.1%

Length

2022-09-04T23:40:08.989285image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:09.086033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ocs2
14.3%
max2
14.3%
tv2
14.3%
тнт1
7.1%
тв-31
7.1%
sbs1
7.1%
tbs1
7.1%
globo1
7.1%
fuji1
7.1%
two1
7.1%

Most occurring characters

ValueCountFrequency (%)
T5
 
10.0%
S5
 
10.0%
5
 
10.0%
Т3
 
6.0%
O3
 
6.0%
a2
 
4.0%
M2
 
4.0%
B2
 
4.0%
C2
 
4.0%
V2
 
4.0%
Other values (17)19
38.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter31
62.0%
Lowercase Letter11
 
22.0%
Space Separator5
 
10.0%
Decimal Number2
 
4.0%
Dash Punctuation1
 
2.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T5
16.1%
S5
16.1%
Т3
9.7%
O3
9.7%
M2
 
6.5%
B2
 
6.5%
C2
 
6.5%
V2
 
6.5%
F1
 
3.2%
L1
 
3.2%
Other values (5)5
16.1%
Lowercase Letter
ValueCountFrequency (%)
a2
18.2%
x2
18.2%
o2
18.2%
i1
9.1%
j1
9.1%
u1
9.1%
l1
9.1%
b1
9.1%
Decimal Number
ValueCountFrequency (%)
31
50.0%
41
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin37
74.0%
Common8
 
16.0%
Cyrillic5
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T5
13.5%
S5
13.5%
O3
 
8.1%
a2
 
5.4%
M2
 
5.4%
B2
 
5.4%
C2
 
5.4%
V2
 
5.4%
x2
 
5.4%
o2
 
5.4%
Other values (10)10
27.0%
Common
ValueCountFrequency (%)
5
62.5%
31
 
12.5%
-1
 
12.5%
41
 
12.5%
Cyrillic
ValueCountFrequency (%)
Т3
60.0%
В1
 
20.0%
Н1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII45
90.0%
Cyrillic5
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T5
 
11.1%
S5
 
11.1%
5
 
11.1%
O3
 
6.7%
a2
 
4.4%
M2
 
4.4%
B2
 
4.4%
C2
 
4.4%
V2
 
4.4%
x2
 
4.4%
Other values (14)15
33.3%
Cyrillic
ValueCountFrequency (%)
Т3
60.0%
В1
 
20.0%
Н1
 
20.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)66.7%
Missing105
Missing (%)92.1%
Memory size1.0 KiB
Russian Federation
Japan
France
Korea, Republic of
Brazil

Length

Max length18
Median length11
Mean length10.33333333
Min length5

Characters and Unicode

Total characters93
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)33.3%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowKorea, Republic of
4th rowJapan
5th rowBrazil

Common Values

ValueCountFrequency (%)
Russian Federation2
 
1.8%
Japan2
 
1.8%
France2
 
1.8%
Korea, Republic of1
 
0.9%
Brazil1
 
0.9%
Netherlands1
 
0.9%
(Missing)105
92.1%

Length

2022-09-04T23:40:09.181035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:09.269035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
russian2
15.4%
federation2
15.4%
japan2
15.4%
france2
15.4%
korea1
7.7%
republic1
7.7%
of1
7.7%
brazil1
7.7%
netherlands1
7.7%

Most occurring characters

ValueCountFrequency (%)
a13
14.0%
e10
 
10.8%
n9
 
9.7%
r7
 
7.5%
i6
 
6.5%
s5
 
5.4%
o4
 
4.3%
4
 
4.3%
F4
 
4.3%
p3
 
3.2%
Other values (15)28
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter76
81.7%
Uppercase Letter12
 
12.9%
Space Separator4
 
4.3%
Other Punctuation1
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a13
17.1%
e10
13.2%
n9
11.8%
r7
9.2%
i6
7.9%
s5
 
6.6%
o4
 
5.3%
p3
 
3.9%
l3
 
3.9%
c3
 
3.9%
Other values (7)13
17.1%
Uppercase Letter
ValueCountFrequency (%)
F4
33.3%
R3
25.0%
J2
16.7%
K1
 
8.3%
B1
 
8.3%
N1
 
8.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin88
94.6%
Common5
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a13
14.8%
e10
11.4%
n9
 
10.2%
r7
 
8.0%
i6
 
6.8%
s5
 
5.7%
o4
 
4.5%
F4
 
4.5%
p3
 
3.4%
l3
 
3.4%
Other values (13)24
27.3%
Common
ValueCountFrequency (%)
4
80.0%
,1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a13
14.0%
e10
 
10.8%
n9
 
9.7%
r7
 
7.5%
i6
 
6.5%
s5
 
5.4%
o4
 
4.3%
4
 
4.3%
F4
 
4.3%
p3
 
3.2%
Other values (15)28
30.1%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)66.7%
Missing105
Missing (%)92.1%
Memory size1.0 KiB
RU
JP
FR
KR
BR

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters18
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)33.3%

Sample

1st rowRU
2nd rowRU
3rd rowKR
4th rowJP
5th rowBR

Common Values

ValueCountFrequency (%)
RU2
 
1.8%
JP2
 
1.8%
FR2
 
1.8%
KR1
 
0.9%
BR1
 
0.9%
NL1
 
0.9%
(Missing)105
92.1%

Length

2022-09-04T23:40:09.352823image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:09.434252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ru2
22.2%
jp2
22.2%
fr2
22.2%
kr1
11.1%
br1
11.1%
nl1
11.1%

Most occurring characters

ValueCountFrequency (%)
R6
33.3%
U2
 
11.1%
J2
 
11.1%
P2
 
11.1%
F2
 
11.1%
K1
 
5.6%
B1
 
5.6%
N1
 
5.6%
L1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter18
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R6
33.3%
U2
 
11.1%
J2
 
11.1%
P2
 
11.1%
F2
 
11.1%
K1
 
5.6%
B1
 
5.6%
N1
 
5.6%
L1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Latin18
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R6
33.3%
U2
 
11.1%
J2
 
11.1%
P2
 
11.1%
F2
 
11.1%
K1
 
5.6%
B1
 
5.6%
N1
 
5.6%
L1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R6
33.3%
U2
 
11.1%
J2
 
11.1%
P2
 
11.1%
F2
 
11.1%
K1
 
5.6%
B1
 
5.6%
N1
 
5.6%
L1
 
5.6%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)66.7%
Missing105
Missing (%)92.1%
Memory size1.0 KiB
Asia/Kamchatka
Asia/Tokyo
Europe/Paris
Asia/Seoul
America/Noronha

Length

Max length16
Median length15
Mean length12.55555556
Min length10

Characters and Unicode

Total characters113
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)33.3%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Seoul
4th rowAsia/Tokyo
5th rowAmerica/Noronha

Common Values

ValueCountFrequency (%)
Asia/Kamchatka2
 
1.8%
Asia/Tokyo2
 
1.8%
Europe/Paris2
 
1.8%
Asia/Seoul1
 
0.9%
America/Noronha1
 
0.9%
Europe/Amsterdam1
 
0.9%
(Missing)105
92.1%

Length

2022-09-04T23:40:09.523636image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:09.616703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka2
22.2%
asia/tokyo2
22.2%
europe/paris2
22.2%
asia/seoul1
11.1%
america/noronha1
11.1%
europe/amsterdam1
11.1%

Most occurring characters

ValueCountFrequency (%)
a16
14.2%
o10
 
8.8%
/9
 
8.0%
s8
 
7.1%
i8
 
7.1%
r8
 
7.1%
A7
 
6.2%
e6
 
5.3%
m5
 
4.4%
k4
 
3.5%
Other values (15)32
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter86
76.1%
Uppercase Letter18
 
15.9%
Other Punctuation9
 
8.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a16
18.6%
o10
11.6%
s8
9.3%
i8
9.3%
r8
9.3%
e6
 
7.0%
m5
 
5.8%
k4
 
4.7%
u4
 
4.7%
c3
 
3.5%
Other values (7)14
16.3%
Uppercase Letter
ValueCountFrequency (%)
A7
38.9%
E3
16.7%
P2
 
11.1%
K2
 
11.1%
T2
 
11.1%
S1
 
5.6%
N1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin104
92.0%
Common9
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a16
15.4%
o10
 
9.6%
s8
 
7.7%
i8
 
7.7%
r8
 
7.7%
A7
 
6.7%
e6
 
5.8%
m5
 
4.8%
k4
 
3.8%
u4
 
3.8%
Other values (14)28
26.9%
Common
ValueCountFrequency (%)
/9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a16
14.2%
o10
 
8.8%
/9
 
8.0%
s8
 
7.1%
i8
 
7.1%
r8
 
7.1%
A7
 
6.2%
e6
 
5.3%
m5
 
4.4%
k4
 
3.5%
Other values (15)32
28.3%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing114
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing109
Missing (%)95.6%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/2309442
https://api.tvmaze.com/episodes/2375640
https://api.tvmaze.com/episodes/2383184
https://api.tvmaze.com/episodes/2383145
https://api.tvmaze.com/episodes/2379702

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2309442
2nd rowhttps://api.tvmaze.com/episodes/2375640
3rd rowhttps://api.tvmaze.com/episodes/2383184
4th rowhttps://api.tvmaze.com/episodes/2383145
5th rowhttps://api.tvmaze.com/episodes/2379702

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094421
 
0.9%
https://api.tvmaze.com/episodes/23756401
 
0.9%
https://api.tvmaze.com/episodes/23831841
 
0.9%
https://api.tvmaze.com/episodes/23831451
 
0.9%
https://api.tvmaze.com/episodes/23797021
 
0.9%
(Missing)109
95.6%

Length

2022-09-04T23:40:09.703702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:09.781982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094421
20.0%
https://api.tvmaze.com/episodes/23756401
20.0%
https://api.tvmaze.com/episodes/23831841
20.0%
https://api.tvmaze.com/episodes/23831451
20.0%
https://api.tvmaze.com/episodes/23797021
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
37
20.0%
27
20.0%
45
14.3%
03
8.6%
73
8.6%
83
8.6%
92
 
5.7%
52
 
5.7%
12
 
5.7%
61
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/20
28.6%
.10
14.3%
37
 
10.0%
27
 
10.0%
45
 
7.1%
:5
 
7.1%
03
 
4.3%
73
 
4.3%
83
 
4.3%
92
 
2.9%
Other values (3)5
 
7.1%
Latin
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing114
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.dvdCountry.name
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing112
Missing (%)98.2%
Memory size1.0 KiB
Korea, Republic of
Japan

Length

Max length18
Median length11.5
Mean length11.5
Min length5

Characters and Unicode

Total characters23
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowKorea, Republic of
2nd rowJapan

Common Values

ValueCountFrequency (%)
Korea, Republic of1
 
0.9%
Japan1
 
0.9%
(Missing)112
98.2%

Length

2022-09-04T23:40:09.873084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:09.948932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
korea1
25.0%
republic1
25.0%
of1
25.0%
japan1
25.0%

Most occurring characters

ValueCountFrequency (%)
a3
13.0%
p2
 
8.7%
e2
 
8.7%
2
 
8.7%
o2
 
8.7%
l1
 
4.3%
J1
 
4.3%
f1
 
4.3%
c1
 
4.3%
i1
 
4.3%
Other values (7)7
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17
73.9%
Uppercase Letter3
 
13.0%
Space Separator2
 
8.7%
Other Punctuation1
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a3
17.6%
p2
11.8%
e2
11.8%
o2
11.8%
l1
 
5.9%
f1
 
5.9%
c1
 
5.9%
i1
 
5.9%
b1
 
5.9%
u1
 
5.9%
Other values (2)2
11.8%
Uppercase Letter
ValueCountFrequency (%)
J1
33.3%
K1
33.3%
R1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20
87.0%
Common3
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a3
15.0%
p2
 
10.0%
e2
 
10.0%
o2
 
10.0%
l1
 
5.0%
J1
 
5.0%
f1
 
5.0%
c1
 
5.0%
i1
 
5.0%
K1
 
5.0%
Other values (5)5
25.0%
Common
ValueCountFrequency (%)
2
66.7%
,1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a3
13.0%
p2
 
8.7%
e2
 
8.7%
2
 
8.7%
o2
 
8.7%
l1
 
4.3%
J1
 
4.3%
f1
 
4.3%
c1
 
4.3%
i1
 
4.3%
Other values (7)7
30.4%

_embedded.show.dvdCountry.code
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing112
Missing (%)98.2%
Memory size1.0 KiB
KR
JP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowKR
2nd rowJP

Common Values

ValueCountFrequency (%)
KR1
 
0.9%
JP1
 
0.9%
(Missing)112
98.2%

Length

2022-09-04T23:40:10.012002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:10.084722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
kr1
50.0%
jp1
50.0%

Most occurring characters

ValueCountFrequency (%)
K1
25.0%
R1
25.0%
J1
25.0%
P1
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K1
25.0%
R1
25.0%
J1
25.0%
P1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K1
25.0%
R1
25.0%
J1
25.0%
P1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K1
25.0%
R1
25.0%
J1
25.0%
P1
25.0%

_embedded.show.dvdCountry.timezone
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing112
Missing (%)98.2%
Memory size1.0 KiB
Asia/Seoul
Asia/Tokyo

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters20
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowAsia/Seoul
2nd rowAsia/Tokyo

Common Values

ValueCountFrequency (%)
Asia/Seoul1
 
0.9%
Asia/Tokyo1
 
0.9%
(Missing)112
98.2%

Length

2022-09-04T23:40:10.271282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:40:10.348005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/seoul1
50.0%
asia/tokyo1
50.0%

Most occurring characters

ValueCountFrequency (%)
o3
15.0%
A2
10.0%
s2
10.0%
i2
10.0%
a2
10.0%
/2
10.0%
S1
 
5.0%
e1
 
5.0%
u1
 
5.0%
l1
 
5.0%
Other values (3)3
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
70.0%
Uppercase Letter4
 
20.0%
Other Punctuation2
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
21.4%
s2
14.3%
i2
14.3%
a2
14.3%
e1
 
7.1%
u1
 
7.1%
l1
 
7.1%
k1
 
7.1%
y1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
A2
50.0%
S1
25.0%
T1
25.0%
Other Punctuation
ValueCountFrequency (%)
/2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin18
90.0%
Common2
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
16.7%
A2
11.1%
s2
11.1%
i2
11.1%
a2
11.1%
S1
 
5.6%
e1
 
5.6%
u1
 
5.6%
l1
 
5.6%
T1
 
5.6%
Other values (2)2
11.1%
Common
ValueCountFrequency (%)
/2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
15.0%
A2
10.0%
s2
10.0%
i2
10.0%
a2
10.0%
/2
10.0%
S1
 
5.0%
e1
 
5.0%
u1
 
5.0%
l1
 
5.0%
Other values (3)3
15.0%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing114
Missing (%)100.0%
Memory size1.0 KiB

Interactions

2022-09-04T23:40:00.183495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:49.907094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.942887image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.983761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.827146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.790026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.687197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.681345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.578486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.424139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.373277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.246665image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.256189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.141991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.013067image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.048757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.896146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.882432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.752809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.752344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.645487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.494139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.438261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.317597image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.331800image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.223600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.090294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.118689image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.972146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.981033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.827023image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.830344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.720587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.572222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.509264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.389968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.406800image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.304383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.166499image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.190090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.044457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.060180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.906322image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.906473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.792587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.757404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.579273image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.456964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.473799image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.377383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.240509image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.259094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.113457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.131186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.980677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.979473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.863586image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.830404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.650194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.522333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.548782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.455278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.318538image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.331088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.184463image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.203181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.054677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.054676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.935586image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.898404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.722195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.589596image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.625664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.530308image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.394538image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.402040image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.253387image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.274984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.127677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.128676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.004703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.970404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.797346image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.770585image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.707098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.601898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.596747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.474038image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.325457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.346980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.203772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.203676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.077141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.042747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.870340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.837579image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.777556image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.667093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.666055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.539215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.390456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.413292image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.273213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.278793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.141208image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.102747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.938272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.902578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.861998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.738713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.742132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.607549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.576588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.479454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.349528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.351333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.209207image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.168765image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.018476image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.969584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.939815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.811689image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.834491image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.681217image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.648793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.548608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.424528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.428333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.280207image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.240755image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.096474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.042494image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:01.019681image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:50.876611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:51.911763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:52.755215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:53.721876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:54.617606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:55.498529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:56.504486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:57.350215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:58.307261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:59.172667image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:40:00.111497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-09-04T23:40:10.432000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-04T23:40:10.659999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-04T23:40:10.893982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-04T23:40:11.169094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-04T23:40:01.296389image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-04T23:40:02.387944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-04T23:40:02.988097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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01988860https://www.tvmaze.com/episodes/1988860/sim-for-you-4x22-chanyeols-episode-22Chanyeol's Episode 22422.0regular2020-12-1506:002020-12-14T21:00:00+00:0016.0NaN<p><b>#Hidden Map Open #Blue Ocean View</b></p>NaNhttps://api.tvmaze.com/episodes/198886041648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/121637[Monday, Wednesday, Friday]NaN30NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNaNNaN361541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpghttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007https://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11987445https://www.tvmaze.com/episodes/1987445/serlok-v-rossii-s01-special-film-o-filmeФильм о фильме1NaNinsignificant_special2020-12-152020-12-15T00:00:00+00:0025.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198744549422https://www.tvmaze.com/shows/49422/serlok-v-rossiiШерлок в РоссииScriptedRussian[Crime, Mystery]To Be Determined52.051.02020-10-22Nonehttps://start.ru/watch/sherlok-v-rossii[Thursday]5.337NaN245.0StartRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNtt11105888https://static.tvmaze.com/uploads/images/medium_portrait/278/695317.jpghttps://static.tvmaze.com/uploads/images/original_untouched/278/695317.jpgNone1643090522https://api.tvmaze.com/shows/49422https://api.tvmaze.com/episodes/1954454NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
22007749https://www.tvmaze.com/episodes/2007749/stand-up-autsajd-1x09-irina-prihodko-skvirtИрина Приходько "Сквирт"19.0regular2020-12-1512:002020-12-15T00:00:00+00:0023.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200774951065https://www.tvmaze.com/shows/51065/stand-up-autsajdStand Up АутсайдVarietyRussian[]Ended40.028.02020-10-132020-12-31https://premier.one/show/13734[Monday]NaN3NaN21.0YouTubeNaNNaNNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpghttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>1616719192https://api.tvmaze.com/shows/51065https://api.tvmaze.com/episodes/2007760NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32008029https://www.tvmaze.com/episodes/2008029/lab-s-antonom-belaevym-2x08-elena-temnikovaЕлена Темникова28.0regular2020-12-152020-12-15T00:00:00+00:0021.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200802952933https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevymLAB с Антоном БеляевымDocumentaryRussian[Music]To Be Determined26.025.02019-12-17Nonehttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva23:45[Saturday]NaN27NaN381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpghttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>1654035738https://api.tvmaze.com/shows/52933https://api.tvmaze.com/episodes/2245512NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/294/737208.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/737208.jpg308.0ТНТRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaN
41964567https://www.tvmaze.com/episodes/1964567/core-sense-1x11-episode-11Episode 11111.0regular2020-12-1510:002020-12-15T02:00:00+00:0024.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196456751336https://www.tvmaze.com/shows/51336/core-senseCore SenseAnimationChinese[Action, Anime, Science-Fiction]Running24.024.02020-10-13Nonehttps://www.bilibili.com/bangumi/media/md2822306410:00[Tuesday]NaN31NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpghttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>1604587119https://api.tvmaze.com/shows/51336https://api.tvmaze.com/episodes/1964569NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52052509https://www.tvmaze.com/episodes/2052509/wu-shen-zhu-zai-1x84-episode-84Episode 84184.0regular2020-12-1510:002020-12-15T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/205250954033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309441NaNNaNNaNNaNNaNNaNNaNNaNNaNhttps://api.tvmaze.com/episodes/2309442NaNNaNNaNNaNNaN
62096297https://www.tvmaze.com/episodes/2096297/no-turning-back-romance-1x03-3313.0regular2020-12-152020-12-15T03:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/209629755002https://www.tvmaze.com/shows/55002/no-turning-back-romanceNo Turning Back RomanceScriptedKorean[]EndedNaN12.02020-12-082021-01-06None[Tuesday, Wednesday]NaN24NaN30.0Naver TVCastKorea, Republic ofKRAsia/Seoulhttps://tv.naver.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/319/799196.jpghttps://static.tvmaze.com/uploads/images/original_untouched/319/799196.jpg<p>A teen romance of So Dam, a sixteen-year-old girl, who has never dated before but she receives her first-ever love confession from a mysterious boy. She is looking for the boy who secretly confessed to her while she was asleep on her desk. The clues include a male voice, mango fruit scent and gym uniform. She must piece the puzzle to find that person among the likely candidates that include hot shots Park Ji Hoo, Jeong Han Kyul, and Joo In Hyuk.</p>1621617231https://api.tvmaze.com/shows/55002https://api.tvmaze.com/episodes/2096309NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
72071479https://www.tvmaze.com/episodes/2071479/youths-in-the-breeze-1x09-people-from-the-story-01PEOPLE FROM THE STORY #0119.0regular2020-12-152020-12-15T04:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/207147954762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuChinaCNAsia/ShanghaiNoneNaNNaN397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
82071480https://www.tvmaze.com/episodes/2071480/youths-in-the-breeze-1x10-people-from-the-story-02PEOPLE FROM THE STORY #02110.0regular2020-12-152020-12-15T04:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/207148054762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuChinaCNAsia/ShanghaiNoneNaNNaN397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92082175https://www.tvmaze.com/episodes/2082175/ling-jian-zun-4x32-di132ji第132集432.0regular2020-12-152020-12-15T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/208217555016https://www.tvmaze.com/shows/55016/ling-jian-zunLing Jian ZunAnimationChinese[Anime]Running10.010.02019-01-15Nonehttps://v.qq.com/x/cover/2w2legt0g8z26al.html[Tuesday, Friday]NaN53NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN364730.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778535.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778535.jpg<p>The strong man was attacked and returned to his youth. He became the weakest waste young lord. He will never let go of the enemy of the previous life in this life and must make up the regret of the previous life in this life! By the time the Spirit Sword is powerful, the protagonist will be supreme in the three worlds between heaven and earth! If there is someone doesn't obey him, he will kill him with the sword!</p><p><br /> </p>1653895786https://api.tvmaze.com/shows/55016https://api.tvmaze.com/episodes/2336755NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

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idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show.webChannel.countryimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone_embedded.show.webChannel
1041991535https://www.tvmaze.com/episodes/1991535/conversa-com-bial-4x152-lazaro-ramosLázaro Ramos4152.0regular2020-12-152020-12-15T14:00:00+00:00NaNNaNNoneNaNhttps://api.tvmaze.com/episodes/199153536813https://www.tvmaze.com/shows/36813/conversa-com-bialConversa com BialTalk ShowPortuguese[]RunningNaN40.02017-05-03Nonehttps://globoplay.globo.com/conversa-com-bial/p/10086/[]NaN6NaN131.0GloboplayBrazilBRAmerica/NoronhaNoneNaNNaN326962.0tt6853288https://static.tvmaze.com/uploads/images/medium_portrait/156/390605.jpghttps://static.tvmaze.com/uploads/images/original_untouched/156/390605.jpgNone1648342248https://api.tvmaze.com/shows/36813https://api.tvmaze.com/episodes/2302125NaNNaNNaN374.0TV GloboBrazilBRAmerica/NoronhaNaNNaNNaNNaNNaNNaNNaN
1052311019https://www.tvmaze.com/episodes/2311019/toki-wo-kakeru-bando-1x09-electric-chahhanElectric Chahhan19.0regular2020-12-1500:252020-12-15T15:25:00+00:0026.0NaN<p>'Yuki Ebana' noticed that the boy who made the 77th song was 'Ryo' when he was young. After returning to her house, Yuki goes to see 'Ryo from the future' who is about to quit her producer, prompted by 'Shiori Kato' and 'Hitoko Murakami'.<br />Ryo tells Yuki, 'My role as a producer is over.' Yuki keeps it, but Ryo says, 'I don't need it anymore,' and further says, 'There is another reason why I came from the future.' The reason was 'to break up with you.' Ryo leaves behind Yuki, saying, 'Congratulations on your debut. You can be the best band.'<br />Yuki, who was told goodbye by Ryo, was depressed. Yuki gets too strong in her practice and runs ahead of herself. Yuki, worried by Shiori and Hitoko, confesses everything. The boy who made her debut song was Ryo, Ryo was Yuki's future husband, and the future with Ryo didn't go well and she was told goodbye. There is a change in the color of the sky that the three people who finished the practice look up at. And also for Ryo's body ...</p>NaNhttps://api.tvmaze.com/episodes/231101961530https://www.tvmaze.com/shows/61530/toki-wo-kakeru-bandoToki wo Kakeru BandoScriptedJapanese[Comedy, Music, Science-Fiction]Ended27.026.02020-10-202020-12-22https://www.fujitv.co.jp/tokikake/00:25[Tuesday]NaN1NaN119.0FODJapanJPAsia/TokyoNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/403/1009836.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009836.jpg<p>A story about Ryo, a mysterious and self-proclaimed music producer from the future, producing a girl band of three girls and leading them to stardom. A comical and tempo conversational drama, and various trials to produce the youth of young people who play music with comedy touch.</p>1649705311https://api.tvmaze.com/shows/61530https://api.tvmaze.com/episodes/2311020NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/403/1009867.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009867.jpg1354.0Fuji TV TWOJapanJPAsia/TokyoNaNNaNNaNJapanJPAsia/TokyoNaN
1062165007https://www.tvmaze.com/episodes/2165007/all-about-android-2020-12-15-stadias-shining-momentStadia's Shining Moment202050.0regular2020-12-152020-12-15T17:00:00+00:0090.0NaNNoneNaNhttps://api.tvmaze.com/episodes/216500717633https://www.tvmaze.com/shows/17633/all-about-androidAll About AndroidNewsEnglish[]RunningNaN90.02011-03-29Nonehttps://twit.tv/shows/all-about-android[Tuesday]NaN45NaN102.0TwitUnited StatesUSAmerica/New_YorkNoneNaNNaN260436.0tt3589312https://static.tvmaze.com/uploads/images/medium_portrait/59/148354.jpghttps://static.tvmaze.com/uploads/images/original_untouched/59/148354.jpg<p><b>All About Android </b>delivers everything you want to know about Android each week -- the biggest news, freshest hardware, best apps and geekiest how-to's -- with Android enthusiasts Jason Howell, Florence Ion, Ron Richards, and a variety of special guests along the way.</p>1653765273https://api.tvmaze.com/shows/17633https://api.tvmaze.com/episodes/2335726NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1071968002https://www.tvmaze.com/episodes/1968002/a-teacher-1x08-episode-8Episode 818.0regular2020-12-152020-12-15T17:00:00+00:0030.0NaN<p>Claire attempts to restart her life. However, not everyone is ready for her to turn the page.</p><p> </p>7.3https://api.tvmaze.com/episodes/196800238339https://www.tvmaze.com/shows/38339/a-teacherA TeacherScriptedEnglish[Drama]EndedNaN27.02020-11-102020-12-29https://www.hulu.com/series/a-teacher-1c871218-05b1-4c66-a22f-260b2cb9bbf9[Tuesday]5.893NaN2.0HuluUnited StatesUSAmerica/New_Yorkhttps://www.hulu.com/NaNNaN352440.0tt10680614https://static.tvmaze.com/uploads/images/medium_portrait/272/681431.jpghttps://static.tvmaze.com/uploads/images/original_untouched/272/681431.jpg<p><b>A Teacher</b> examines the complexities and consequences of an illegal relationship between a female teacher, Claire and her male high school student, Eric. Dissatisfied in their own lives, Claire and Eric discover an undeniable escape in each other, but their relationship accelerates faster than anticipated and the permanent damage becomes impossible to ignore.</p>1637344861https://api.tvmaze.com/shows/38339https://api.tvmaze.com/episodes/1968004NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/287/717676.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/717676.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1082215235https://www.tvmaze.com/episodes/2215235/comedy-central-stand-up-featuring-7x02-christi-chiello-reasons-not-to-be-a-mom-to-human-babiesChristi Chiello - Reasons Not to Be a Mom to Human Babies72.0regular2020-12-152020-12-15T17:00:00+00:00NaNNaN<p>Christi Chiello discusses becoming an aunt and a cat mom, and explains why she loves not having children.</p>NaNhttps://api.tvmaze.com/episodes/221523540862https://www.tvmaze.com/shows/40862/comedy-central-stand-up-featuringComedy Central Stand-Up FeaturingVarietyEnglish[Comedy]RunningNaNNaN2019-01-11Nonehttp://www.cc.com/shows/comedy-central-stand-up-featuring[Friday]NaN38NaN73.0CC: StudiosUnited StatesUSAmerica/New_YorkNoneNaNNaN358389.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/378/946750.jpghttps://static.tvmaze.com/uploads/images/original_untouched/378/946750.jpg<p>Get your stand-up fix from today's freshest young comedians as Comedy Central introduces you to up-and-coming comics, who are serving up quick hits of their sets.</p>1656505253https://api.tvmaze.com/shows/40862https://api.tvmaze.com/episodes/2354757NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/378/946851.jpghttps://static.tvmaze.com/uploads/images/original_untouched/378/946851.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1092380807https://www.tvmaze.com/episodes/2380807/dimension-20s-adventuring-party-3x04-the-perfect-stack-of-pancakesThe Perfect Stack of Pancakes34.0regular2020-12-152020-12-15T17:00:00+00:0057.0NaNNoneNaNhttps://api.tvmaze.com/episodes/238080763761https://www.tvmaze.com/shows/63761/dimension-20s-adventuring-partyDimension 20's Adventuring PartyTalk ShowEnglish[]Running57.057.02020-04-08NoneNone[]NaN27NaN311.0DropoutUnited StatesUSAmerica/New_YorkNoneNaNNaN391568.0tt13280542https://static.tvmaze.com/uploads/images/medium_portrait/420/1050072.jpghttps://static.tvmaze.com/uploads/images/original_untouched/420/1050072.jpg<p>Adventuring Party is a series of livestreamed talk-back episodes that aired after each new episode of A Crown of Candy. An additional episode was pre-recorded featuring the Pirates of Leviathan following the release of episode 4. Each Adventuring Party episode features the Dimension 20 cast as they talk about the events of the most recent episode, their experiences during that session, any unique challenges or situations they encountered, and answer as many fan questions as Brennan allows.</p><p><br /> </p>1661532809https://api.tvmaze.com/shows/63761https://api.tvmaze.com/episodes/2380882NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1101977413https://www.tvmaze.com/episodes/1977413/goede-tijden-slechte-tijden-31x62-aflevering-6317Aflevering 63173162.0regular2020-12-1520:002020-12-15T19:00:00+00:0023.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19774132504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch[Drama, Romance]Running23.025.01990-10-01Nonehttp://gtst.nl/#!/20:00[Monday, Tuesday, Wednesday, Thursday]NaN84NaNNaNNaNNaNNaNNaNNaNNaN19056.0104271.0tt0096597https://static.tvmaze.com/uploads/images/medium_portrait/332/830481.jpghttps://static.tvmaze.com/uploads/images/original_untouched/332/830481.jpgNone1662346277https://api.tvmaze.com/shows/2504https://api.tvmaze.com/episodes/2379701NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/288/720706.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/720706.jpg112.0RTL4NetherlandsNLEurope/AmsterdamNaNhttps://api.tvmaze.com/episodes/2379702NaNNaNNaNNaNNaN
1111976933https://www.tvmaze.com/episodes/1976933/cheyenne-et-lola-1x07-romanceRomance17.0regular2020-12-1520:402020-12-15T19:40:00+00:0050.0NaN<p>Contre toute attente, Yannick et Lola tombent sincèrement amoureux l'un de l'autre.</p>NaNhttps://api.tvmaze.com/episodes/197693350106https://www.tvmaze.com/shows/50106/cheyenne-et-lolaCheyenne et LolaScriptedFrench[Drama, Comedy, Crime]Running50.050.02020-11-24Nonehttps://go.ocs.fr/details/serie/PSCHEYENNEEW016825920:40[Tuesday]NaN40NaNNaNNaNNaNNaNNaNNaNNaNNaN281345.0tt10094402https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>1644650582https://api.tvmaze.com/shows/50106https://api.tvmaze.com/episodes/1976934NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/289/724607.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724607.jpg432.0OCS MaxFranceFREurope/ParisNaNNaNNaNNaNNaNNaNNaN
1121976934https://www.tvmaze.com/episodes/1976934/cheyenne-et-lola-1x08-plus-dure-sera-la-chutePlus dure sera la chute18.0regular2020-12-1520:402020-12-15T19:40:00+00:0050.0NaN<p>Pour aider Cheyenne à libérer les migrantes, Lola fait croire à Yannick que Babette l'a agressée.</p>NaNhttps://api.tvmaze.com/episodes/197693450106https://www.tvmaze.com/shows/50106/cheyenne-et-lolaCheyenne et LolaScriptedFrench[Drama, Comedy, Crime]Running50.050.02020-11-24Nonehttps://go.ocs.fr/details/serie/PSCHEYENNEEW016825920:40[Tuesday]NaN40NaNNaNNaNNaNNaNNaNNaNNaNNaN281345.0tt10094402https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>1644650582https://api.tvmaze.com/shows/50106https://api.tvmaze.com/episodes/1976934NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/289/724608.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724608.jpg432.0OCS MaxFranceFREurope/ParisNaNNaNNaNNaNNaNNaNNaN
1131987429https://www.tvmaze.com/episodes/1987429/chicken-girls-7x15-attaway-dayAttaway Day715.0regular2020-12-1515:002020-12-15T20:00:00+00:0016.0NaN<p>In the season finale, Harmony finds her flock, while Rhyme reconnects with old friends. </p>NaNhttps://api.tvmaze.com/episodes/198742932087https://www.tvmaze.com/shows/32087/chicken-girlsChicken GirlsScriptedEnglish[Drama, Music]RunningNaN14.02017-09-05Nonehttps://www.youtube.com/playlist?list=PLVewHiZp3_LPhqzbcZFmS3iuDm9HymTsy15:00[Tuesday]5.690NaN274.0BratUnited StatesUSAmerica/New_YorkNoneNaNNaN339854.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888874.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888874.jpg<p>Rhyme and her friends — known by their 'ship name, "The Chicken Girls" — have been dancing together forever. But this year, everything's changing...</p>1661790437https://api.tvmaze.com/shows/32087https://api.tvmaze.com/episodes/2270191NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/369/923711.jpghttps://static.tvmaze.com/uploads/images/original_untouched/369/923711.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN